Overview

Dataset statistics

Number of variables345
Number of observations50000
Missing cells1344546
Missing cells (%)7.8%
Total size in memory131.6 MiB
Average record size in memory2.7 KiB

Variable types

Numeric342
Categorical3

Alerts

Agri_1m has constant value "0"Constant
Cash_1m has constant value "0"Constant
Agri_amt_1m has constant value "0"Constant
Cash_amt_1m has constant value "0"Constant
Agri_3m has constant value "0"Constant
Cash_3m has constant value "0"Constant
Agri_amt_3m has constant value "0"Constant
Cash_amt_3m has constant value "0"Constant
Agri_6m has constant value "0"Constant
Cash_6m has constant value "0"Constant
Agri_amt_6m has constant value "0"Constant
Cash_amt_6m has constant value "0"Constant
Agri_12m has constant value "0"Constant
Cash_12m has constant value "0"Constant
Agri_amt_12m has constant value "0"Constant
Cash_amt_12m has constant value "0"Constant
has_taken_emi_before has constant value "1.0"Constant
married_flag has constant value "0"Constant
merchant_country has a high cardinality: 66 distinct valuesHigh cardinality
merchant_country is highly imbalanced (95.1%)Imbalance
revolve_1m has 3421 (6.8%) missing valuesMissing
revolve_3m has 3421 (6.8%) missing valuesMissing
revolve_6m has 3421 (6.8%) missing valuesMissing
util_1m has 3430 (6.9%) missing valuesMissing
util_3m has 3421 (6.8%) missing valuesMissing
util_6m has 3421 (6.8%) missing valuesMissing
payment_ratio_1m has 8889 (17.8%) missing valuesMissing
payment_ratio_3m has 6990 (14.0%) missing valuesMissing
payment_ratio_6m has 6536 (13.1%) missing valuesMissing
paymad_1m has 11185 (22.4%) missing valuesMissing
paymad_3m has 7859 (15.7%) missing valuesMissing
paymad_6m has 7026 (14.1%) missing valuesMissing
has_taken_emi_before has 39958 (79.9%) missing valuesMissing
count_of_emi_before has 39958 (79.9%) missing valuesMissing
Bureau_AL_amt_ever has 38351 (76.7%) missing valuesMissing
Bureau_BL_amt_ever has 45820 (91.6%) missing valuesMissing
Bureau_CCOD_amt_ever has 16336 (32.7%) missing valuesMissing
Bureau_CV_amt_ever has 49226 (98.5%) missing valuesMissing
Bureau_CD_amt_ever has 30347 (60.7%) missing valuesMissing
Bureau_EL_amt_ever has 47414 (94.8%) missing valuesMissing
Bureau_GL_amt_ever has 45582 (91.2%) missing valuesMissing
Bureau_HL_amt_ever has 36745 (73.5%) missing valuesMissing
Bureau_PL_amt_ever has 32769 (65.5%) missing valuesMissing
Bureau_LAP_amt_ever has 46674 (93.3%) missing valuesMissing
Bureau_TW_amt_ever has 42804 (85.6%) missing valuesMissing
Bureau_UC_amt_ever has 48507 (97.0%) missing valuesMissing
Bureau_unsec_amt_ever has 27999 (56.0%) missing valuesMissing
Bureau_sec_amt_ever has 34778 (69.6%) missing valuesMissing
Bureau_all_amt_ever has 11400 (22.8%) missing valuesMissing
Bureau_AL_amt_live has 44638 (89.3%) missing valuesMissing
Bureau_BL_amt_live has 47622 (95.2%) missing valuesMissing
Bureau_CCOD_amt_live has 17781 (35.6%) missing valuesMissing
Bureau_CV_amt_live has 49629 (99.3%) missing valuesMissing
Bureau_CD_amt_live has 39553 (79.1%) missing valuesMissing
Bureau_EL_amt_live has 49215 (98.4%) missing valuesMissing
Bureau_GL_amt_live has 48446 (96.9%) missing valuesMissing
Bureau_HL_amt_live has 41205 (82.4%) missing valuesMissing
Bureau_PL_amt_live has 38188 (76.4%) missing valuesMissing
Bureau_LAP_amt_live has 47695 (95.4%) missing valuesMissing
Bureau_TW_amt_live has 47935 (95.9%) missing valuesMissing
Bureau_UC_amt_live has 49252 (98.5%) missing valuesMissing
Bureau_unsec_amt_live has 35278 (70.6%) missing valuesMissing
Bureau_sec_amt_live has 39799 (79.6%) missing valuesMissing
Bureau_all_amt_live has 13450 (26.9%) missing valuesMissing
avg_sa_balance_1m has 3108 (6.2%) missing valuesMissing
avg_sa_balance_3m has 3108 (6.2%) missing valuesMissing
avg_sa_balance_6m has 3108 (6.2%) missing valuesMissing
avg_sa_balance_12m has 3108 (6.2%) missing valuesMissing
pctchg_curr_sa_bal_avg_sa_bal_1m has 5667 (11.3%) missing valuesMissing
pctchg_curr_sa_bal_avg_sa_bal_3m has 5808 (11.6%) missing valuesMissing
pctchg_curr_sa_bal_avg_sa_bal_6m has 7201 (14.4%) missing valuesMissing
Contract_1m is highly skewed (γ1 = 37.91046285)Skewed
Airline_1m is highly skewed (γ1 = 21.70080878)Skewed
Insurance_1m is highly skewed (γ1 = 35.09705685)Skewed
Railways_1m is highly skewed (γ1 = 24.6112462)Skewed
Airports_1m is highly skewed (γ1 = 67.35704306)Skewed
Retail_1m is highly skewed (γ1 = 42.86004666)Skewed
Auto_1m is highly skewed (γ1 = 30.78082838)Skewed
MusicStores_1m is highly skewed (γ1 = 55.36205687)Skewed
Books_1m is highly skewed (γ1 = 24.29408508)Skewed
DirectM_1m is highly skewed (γ1 = 20.70773763)Skewed
QuasiCash_1m is highly skewed (γ1 = 70.69349454)Skewed
FS_1m is highly skewed (γ1 = 41.48785106)Skewed
ProfServ_1m is highly skewed (γ1 = 27.49568756)Skewed
Education_1m is highly skewed (γ1 = 29.11196446)Skewed
GovtServices_1m is highly skewed (γ1 = 35.99012688)Skewed
Contract_amt_1m is highly skewed (γ1 = 64.54806412)Skewed
Airline_amt_1m is highly skewed (γ1 = 23.81293327)Skewed
Insurance_amt_1m is highly skewed (γ1 = 24.36113882)Skewed
Hotels_amt_1m is highly skewed (γ1 = 37.30334908)Skewed
Airports_amt_1m is highly skewed (γ1 = 50.09701966)Skewed
Medical_amt_1m is highly skewed (γ1 = 23.06243138)Skewed
DeptStores_amt_1m is highly skewed (γ1 = 24.24559308)Skewed
Food_amt_1m is highly skewed (γ1 = 35.66319458)Skewed
Auto_amt_1m is highly skewed (γ1 = 28.59649908)Skewed
MiscServices_amt_1m is highly skewed (γ1 = 23.69752565)Skewed
HomeF_amt_1m is highly skewed (γ1 = 44.04943211)Skewed
MusicStores_amt_1m is highly skewed (γ1 = 68.34431396)Skewed
DigitalGoods_amt_1m is highly skewed (γ1 = 32.85823397)Skewed
Alcohol_amt_1m is highly skewed (γ1 = 35.180207)Skewed
Books_amt_1m is highly skewed (γ1 = 40.21348698)Skewed
Jewelry_amt_1m is highly skewed (γ1 = 22.24473852)Skewed
DirectM_amt_1m is highly skewed (γ1 = 102.1207067)Skewed
QuasiCash_amt_1m is highly skewed (γ1 = 149.0971175)Skewed
FS_amt_1m is highly skewed (γ1 = 41.48785106)Skewed
WalletLoad_amt_1m is highly skewed (γ1 = 29.75791273)Skewed
BusinessServ_amt_1m is highly skewed (γ1 = 42.98173804)Skewed
ProfServ_amt_1m is highly skewed (γ1 = 36.72967912)Skewed
GovtServices_amt_1m is highly skewed (γ1 = 37.02388523)Skewed
Contract_3m is highly skewed (γ1 = 34.78914986)Skewed
Airline_3m is highly skewed (γ1 = 29.50974303)Skewed
transport_3m is highly skewed (γ1 = 21.19144641)Skewed
Insurance_3m is highly skewed (γ1 = 51.17353581)Skewed
Airports_3m is highly skewed (γ1 = 46.50959616)Skewed
Retail_3m is highly skewed (γ1 = 52.81860742)Skewed
Auto_3m is highly skewed (γ1 = 28.46302955)Skewed
MusicStores_3m is highly skewed (γ1 = 87.28925641)Skewed
DigitalGoods_3m is highly skewed (γ1 = 22.67581288)Skewed
Books_3m is highly skewed (γ1 = 57.77552351)Skewed
DirectM_3m is highly skewed (γ1 = 21.74502737)Skewed
QuasiCash_3m is highly skewed (γ1 = 77.89338677)Skewed
FS_3m is highly skewed (γ1 = 26.86414644)Skewed
ProfServ_3m is highly skewed (γ1 = 20.80803992)Skewed
Education_3m is highly skewed (γ1 = 22.97968228)Skewed
GovtServices_3m is highly skewed (γ1 = 47.9914472)Skewed
Contract_amt_3m is highly skewed (γ1 = 45.61014742)Skewed
Airline_amt_3m is highly skewed (γ1 = 30.18308024)Skewed
transport_amt_3m is highly skewed (γ1 = 20.68576257)Skewed
Insurance_amt_3m is highly skewed (γ1 = 34.35284618)Skewed
Hotels_amt_3m is highly skewed (γ1 = 42.77689715)Skewed
Airports_amt_3m is highly skewed (γ1 = 52.14727746)Skewed
Utility_amt_3m is highly skewed (γ1 = 21.14555362)Skewed
Medical_amt_3m is highly skewed (γ1 = 28.47865804)Skewed
Food_amt_3m is highly skewed (γ1 = 49.93555124)Skewed
Auto_amt_3m is highly skewed (γ1 = 25.52549873)Skewed
MiscServices_amt_3m is highly skewed (γ1 = 30.16463497)Skewed
HomeF_amt_3m is highly skewed (γ1 = 26.28062187)Skewed
MusicStores_amt_3m is highly skewed (γ1 = 80.00078775)Skewed
Restaurants_amt_3m is highly skewed (γ1 = 20.79086653)Skewed
DigitalGoods_amt_3m is highly skewed (γ1 = 21.24664222)Skewed
Alcohol_amt_3m is highly skewed (γ1 = 32.97707862)Skewed
Books_amt_3m is highly skewed (γ1 = 52.38559939)Skewed
DirectM_amt_3m is highly skewed (γ1 = 97.61371505)Skewed
QuasiCash_amt_3m is highly skewed (γ1 = 148.9790539)Skewed
FS_amt_3m is highly skewed (γ1 = 159.7054686)Skewed
WalletLoad_amt_3m is highly skewed (γ1 = 38.26647813)Skewed
BusinessServ_amt_3m is highly skewed (γ1 = 28.70445734)Skewed
ProfServ_amt_3m is highly skewed (γ1 = 26.89576097)Skewed
GovtServices_amt_3m is highly skewed (γ1 = 37.52586981)Skewed
Contract_6m is highly skewed (γ1 = 34.78914986)Skewed
Airline_6m is highly skewed (γ1 = 29.50974303)Skewed
transport_6m is highly skewed (γ1 = 21.19144641)Skewed
Insurance_6m is highly skewed (γ1 = 51.17353581)Skewed
Airports_6m is highly skewed (γ1 = 46.50959616)Skewed
Retail_6m is highly skewed (γ1 = 52.81860742)Skewed
Auto_6m is highly skewed (γ1 = 28.46302955)Skewed
MusicStores_6m is highly skewed (γ1 = 87.28925641)Skewed
DigitalGoods_6m is highly skewed (γ1 = 22.67581288)Skewed
Books_6m is highly skewed (γ1 = 57.77552351)Skewed
DirectM_6m is highly skewed (γ1 = 21.74502737)Skewed
QuasiCash_6m is highly skewed (γ1 = 77.89338677)Skewed
FS_6m is highly skewed (γ1 = 26.86414644)Skewed
ProfServ_6m is highly skewed (γ1 = 20.80803992)Skewed
Education_6m is highly skewed (γ1 = 22.97968228)Skewed
GovtServices_6m is highly skewed (γ1 = 47.9914472)Skewed
Contract_amt_6m is highly skewed (γ1 = 45.61014742)Skewed
Airline_amt_6m is highly skewed (γ1 = 30.18308024)Skewed
transport_amt_6m is highly skewed (γ1 = 20.68576257)Skewed
Insurance_amt_6m is highly skewed (γ1 = 34.35284618)Skewed
Hotels_amt_6m is highly skewed (γ1 = 42.77689715)Skewed
Airports_amt_6m is highly skewed (γ1 = 52.14727746)Skewed
Utility_amt_6m is highly skewed (γ1 = 21.14555362)Skewed
Medical_amt_6m is highly skewed (γ1 = 28.47865804)Skewed
Food_amt_6m is highly skewed (γ1 = 49.93555124)Skewed
Auto_amt_6m is highly skewed (γ1 = 25.52549873)Skewed
MiscServices_amt_6m is highly skewed (γ1 = 30.16463497)Skewed
HomeF_amt_6m is highly skewed (γ1 = 26.28062187)Skewed
MusicStores_amt_6m is highly skewed (γ1 = 80.00078775)Skewed
Restaurants_amt_6m is highly skewed (γ1 = 20.79086653)Skewed
DigitalGoods_amt_6m is highly skewed (γ1 = 21.24664222)Skewed
Alcohol_amt_6m is highly skewed (γ1 = 32.97707862)Skewed
Books_amt_6m is highly skewed (γ1 = 52.38559939)Skewed
DirectM_amt_6m is highly skewed (γ1 = 97.61371505)Skewed
QuasiCash_amt_6m is highly skewed (γ1 = 148.9790539)Skewed
FS_amt_6m is highly skewed (γ1 = 159.7054686)Skewed
WalletLoad_amt_6m is highly skewed (γ1 = 38.26647813)Skewed
BusinessServ_amt_6m is highly skewed (γ1 = 28.70445734)Skewed
ProfServ_amt_6m is highly skewed (γ1 = 26.89576097)Skewed
GovtServices_amt_6m is highly skewed (γ1 = 37.52586981)Skewed
Contract_12m is highly skewed (γ1 = 34.78914986)Skewed
Airline_12m is highly skewed (γ1 = 29.50974303)Skewed
transport_12m is highly skewed (γ1 = 21.19144641)Skewed
Insurance_12m is highly skewed (γ1 = 51.17353581)Skewed
Airports_12m is highly skewed (γ1 = 46.50959616)Skewed
Retail_12m is highly skewed (γ1 = 52.81860742)Skewed
Auto_12m is highly skewed (γ1 = 28.46302955)Skewed
MusicStores_12m is highly skewed (γ1 = 87.28925641)Skewed
DigitalGoods_12m is highly skewed (γ1 = 22.67581288)Skewed
Books_12m is highly skewed (γ1 = 57.77552351)Skewed
DirectM_12m is highly skewed (γ1 = 21.74502737)Skewed
QuasiCash_12m is highly skewed (γ1 = 77.89338677)Skewed
FS_12m is highly skewed (γ1 = 26.86414644)Skewed
ProfServ_12m is highly skewed (γ1 = 20.80803992)Skewed
Education_12m is highly skewed (γ1 = 22.97968228)Skewed
GovtServices_12m is highly skewed (γ1 = 47.9914472)Skewed
Contract_amt_12m is highly skewed (γ1 = 45.61014742)Skewed
Airline_amt_12m is highly skewed (γ1 = 30.18308024)Skewed
transport_amt_12m is highly skewed (γ1 = 20.68576257)Skewed
Insurance_amt_12m is highly skewed (γ1 = 34.35284618)Skewed
Hotels_amt_12m is highly skewed (γ1 = 42.77689715)Skewed
Airports_amt_12m is highly skewed (γ1 = 52.14727746)Skewed
Utility_amt_12m is highly skewed (γ1 = 21.14555362)Skewed
Medical_amt_12m is highly skewed (γ1 = 28.47865804)Skewed
Food_amt_12m is highly skewed (γ1 = 49.93555124)Skewed
Auto_amt_12m is highly skewed (γ1 = 25.52549873)Skewed
MiscServices_amt_12m is highly skewed (γ1 = 30.16463497)Skewed
HomeF_amt_12m is highly skewed (γ1 = 26.28062187)Skewed
MusicStores_amt_12m is highly skewed (γ1 = 80.00078775)Skewed
Restaurants_amt_12m is highly skewed (γ1 = 20.79086653)Skewed
DigitalGoods_amt_12m is highly skewed (γ1 = 21.24664222)Skewed
Alcohol_amt_12m is highly skewed (γ1 = 32.97707862)Skewed
Books_amt_12m is highly skewed (γ1 = 52.38559939)Skewed
DirectM_amt_12m is highly skewed (γ1 = 97.61371505)Skewed
QuasiCash_amt_12m is highly skewed (γ1 = 148.9790539)Skewed
FS_amt_12m is highly skewed (γ1 = 159.7054686)Skewed
WalletLoad_amt_12m is highly skewed (γ1 = 38.26647813)Skewed
BusinessServ_amt_12m is highly skewed (γ1 = 28.70445734)Skewed
ProfServ_amt_12m is highly skewed (γ1 = 26.89576097)Skewed
GovtServices_amt_12m is highly skewed (γ1 = 37.52586981)Skewed
spends_1m is highly skewed (γ1 = 24.86908428)Skewed
spends_3m is highly skewed (γ1 = 22.86820727)Skewed
spends_6m is highly skewed (γ1 = 22.86820727)Skewed
spends_12m is highly skewed (γ1 = 22.86820727)Skewed
payment_ratio_1m is highly skewed (γ1 = -59.29663513)Skewed
payment_ratio_3m is highly skewed (γ1 = -81.408264)Skewed
payment_ratio_6m is highly skewed (γ1 = -84.26270787)Skewed
paymad_1m is highly skewed (γ1 = 111.890308)Skewed
paymad_3m is highly skewed (γ1 = 61.85228678)Skewed
paymad_6m is highly skewed (γ1 = 62.45375746)Skewed
Bureau_AL_amt_ever is highly skewed (γ1 = 47.93700845)Skewed
Bureau_BL_amt_ever is highly skewed (γ1 = 23.55052485)Skewed
Bureau_CCOD_amt_ever is highly skewed (γ1 = 147.7545679)Skewed
Bureau_CD_amt_ever is highly skewed (γ1 = 115.2986889)Skewed
Bureau_PL_amt_ever is highly skewed (γ1 = 42.03517517)Skewed
Bureau_unsec_amt_ever is highly skewed (γ1 = 31.55790447)Skewed
Bureau_all_amt_ever is highly skewed (γ1 = 25.67655087)Skewed
Bureau_AL_amt_live is highly skewed (γ1 = 27.28540456)Skewed
Bureau_BL_amt_live is highly skewed (γ1 = 24.58258982)Skewed
Bureau_CCOD_amt_live is highly skewed (γ1 = 101.0823389)Skewed
Bureau_CD_amt_live is highly skewed (γ1 = 32.80678197)Skewed
Bureau_PL_amt_live is highly skewed (γ1 = 22.16304126)Skewed
Bureau_unsec_amt_live is highly skewed (γ1 = 35.10120566)Skewed
Bureau_all_amt_live is highly skewed (γ1 = 33.13915118)Skewed
avg_sa_balance_1m is highly skewed (γ1 = 38.79019486)Skewed
avg_sa_balance_3m is highly skewed (γ1 = 22.52760448)Skewed
avg_sa_balance_12m is highly skewed (γ1 = 23.02572902)Skewed
pctchg_curr_sa_bal_avg_sa_bal_1m is highly skewed (γ1 = 108.9881541)Skewed
pctchg_curr_sa_bal_avg_sa_bal_3m is highly skewed (γ1 = 142.5027904)Skewed
pctchg_curr_sa_bal_avg_sa_bal_6m is highly skewed (γ1 = 136.5094811)Skewed
target_variable has 47380 (94.8%) zerosZeros
Agri_1m has 50000 (100.0%) zerosZeros
Contract_1m has 49798 (99.6%) zerosZeros
Airline_1m has 47940 (95.9%) zerosZeros
transport_1m has 42622 (85.2%) zerosZeros
Insurance_1m has 43650 (87.3%) zerosZeros
Hotels_1m has 42350 (84.7%) zerosZeros
Railways_1m has 43568 (87.1%) zerosZeros
Airports_1m has 49969 (99.9%) zerosZeros
Utility_1m has 29041 (58.1%) zerosZeros
Retail_1m has 33810 (67.6%) zerosZeros
Medical_1m has 38877 (77.8%) zerosZeros
Fuel_1m has 27687 (55.4%) zerosZeros
DeptStores_1m has 27906 (55.8%) zerosZeros
Food_1m has 40586 (81.2%) zerosZeros
Auto_1m has 47966 (95.9%) zerosZeros
ClothStores_1m has 31985 (64.0%) zerosZeros
MiscServices_1m has 41405 (82.8%) zerosZeros
HomeF_1m has 48659 (97.3%) zerosZeros
Electronics_1m has 38735 (77.5%) zerosZeros
MusicStores_1m has 49582 (99.2%) zerosZeros
Restaurants_1m has 27910 (55.8%) zerosZeros
DigitalGoods_1m has 46387 (92.8%) zerosZeros
Alcohol_1m has 46220 (92.4%) zerosZeros
Books_1m has 47598 (95.2%) zerosZeros
Jewelry_1m has 47539 (95.1%) zerosZeros
DirectM_1m has 48713 (97.4%) zerosZeros
Cash_1m has 50000 (100.0%) zerosZeros
QuasiCash_1m has 49979 (> 99.9%) zerosZeros
FS_1m has 49971 (99.9%) zerosZeros
RentPayments_1m has 41830 (83.7%) zerosZeros
WalletLoad_1m has 43000 (86.0%) zerosZeros
BusinessServ_1m has 36948 (73.9%) zerosZeros
ProfServ_1m has 47143 (94.3%) zerosZeros
Education_1m has 44712 (89.4%) zerosZeros
GovtServices_1m has 41869 (83.7%) zerosZeros
Agri_amt_1m has 50000 (100.0%) zerosZeros
Contract_amt_1m has 49798 (99.6%) zerosZeros
Airline_amt_1m has 47940 (95.9%) zerosZeros
transport_amt_1m has 42622 (85.2%) zerosZeros
Insurance_amt_1m has 43650 (87.3%) zerosZeros
Hotels_amt_1m has 42350 (84.7%) zerosZeros
Railways_amt_1m has 43568 (87.1%) zerosZeros
Airports_amt_1m has 49969 (99.9%) zerosZeros
Utility_amt_1m has 29041 (58.1%) zerosZeros
Retail_amt_1m has 33810 (67.6%) zerosZeros
Medical_amt_1m has 38877 (77.8%) zerosZeros
Fuel_amt_1m has 27687 (55.4%) zerosZeros
DeptStores_amt_1m has 27906 (55.8%) zerosZeros
Food_amt_1m has 40586 (81.2%) zerosZeros
Auto_amt_1m has 47966 (95.9%) zerosZeros
ClothStores_amt_1m has 31985 (64.0%) zerosZeros
MiscServices_amt_1m has 41405 (82.8%) zerosZeros
HomeF_amt_1m has 48659 (97.3%) zerosZeros
Electronics_amt_1m has 38735 (77.5%) zerosZeros
MusicStores_amt_1m has 49582 (99.2%) zerosZeros
Restaurants_amt_1m has 27910 (55.8%) zerosZeros
DigitalGoods_amt_1m has 46387 (92.8%) zerosZeros
Alcohol_amt_1m has 46220 (92.4%) zerosZeros
Books_amt_1m has 47598 (95.2%) zerosZeros
Jewelry_amt_1m has 47539 (95.1%) zerosZeros
DirectM_amt_1m has 48713 (97.4%) zerosZeros
Cash_amt_1m has 50000 (100.0%) zerosZeros
QuasiCash_amt_1m has 49979 (> 99.9%) zerosZeros
FS_amt_1m has 49971 (99.9%) zerosZeros
RentPayments_amt_1m has 41830 (83.7%) zerosZeros
WalletLoad_amt_1m has 43000 (86.0%) zerosZeros
BusinessServ_amt_1m has 36948 (73.9%) zerosZeros
ProfServ_amt_1m has 47143 (94.3%) zerosZeros
Education_amt_1m has 44712 (89.4%) zerosZeros
GovtServices_amt_1m has 41869 (83.7%) zerosZeros
Agri_3m has 50000 (100.0%) zerosZeros
Contract_3m has 49536 (99.1%) zerosZeros
Airline_3m has 46359 (92.7%) zerosZeros
transport_3m has 37570 (75.1%) zerosZeros
Insurance_3m has 39445 (78.9%) zerosZeros
Hotels_3m has 36891 (73.8%) zerosZeros
Railways_3m has 39278 (78.6%) zerosZeros
Airports_3m has 49945 (99.9%) zerosZeros
Utility_3m has 20688 (41.4%) zerosZeros
Retail_3m has 25725 (51.4%) zerosZeros
Medical_3m has 32314 (64.6%) zerosZeros
Fuel_3m has 21967 (43.9%) zerosZeros
DeptStores_3m has 20359 (40.7%) zerosZeros
Food_3m has 34180 (68.4%) zerosZeros
Auto_3m has 46021 (92.0%) zerosZeros
ClothStores_3m has 24277 (48.6%) zerosZeros
MiscServices_3m has 34785 (69.6%) zerosZeros
HomeF_3m has 47285 (94.6%) zerosZeros
Electronics_3m has 32112 (64.2%) zerosZeros
MusicStores_3m has 49307 (98.6%) zerosZeros
Restaurants_3m has 20254 (40.5%) zerosZeros
DigitalGoods_3m has 44043 (88.1%) zerosZeros
Alcohol_3m has 43436 (86.9%) zerosZeros
Books_3m has 45427 (90.9%) zerosZeros
Jewelry_3m has 44421 (88.8%) zerosZeros
DirectM_3m has 47389 (94.8%) zerosZeros
Cash_3m has 50000 (100.0%) zerosZeros
QuasiCash_3m has 49969 (99.9%) zerosZeros
FS_3m has 49931 (99.9%) zerosZeros
RentPayments_3m has 38583 (77.2%) zerosZeros
WalletLoad_3m has 39449 (78.9%) zerosZeros
BusinessServ_3m has 28973 (57.9%) zerosZeros
ProfServ_3m has 44022 (88.0%) zerosZeros
Education_3m has 41554 (83.1%) zerosZeros
GovtServices_3m has 36573 (73.1%) zerosZeros
Agri_amt_3m has 50000 (100.0%) zerosZeros
Contract_amt_3m has 49536 (99.1%) zerosZeros
Airline_amt_3m has 46359 (92.7%) zerosZeros
transport_amt_3m has 37570 (75.1%) zerosZeros
Insurance_amt_3m has 39445 (78.9%) zerosZeros
Hotels_amt_3m has 36891 (73.8%) zerosZeros
Railways_amt_3m has 39278 (78.6%) zerosZeros
Airports_amt_3m has 49945 (99.9%) zerosZeros
Utility_amt_3m has 20688 (41.4%) zerosZeros
Retail_amt_3m has 25725 (51.4%) zerosZeros
Medical_amt_3m has 32314 (64.6%) zerosZeros
Fuel_amt_3m has 21967 (43.9%) zerosZeros
DeptStores_amt_3m has 20359 (40.7%) zerosZeros
Food_amt_3m has 34180 (68.4%) zerosZeros
Auto_amt_3m has 46021 (92.0%) zerosZeros
ClothStores_amt_3m has 24277 (48.6%) zerosZeros
MiscServices_amt_3m has 34785 (69.6%) zerosZeros
HomeF_amt_3m has 47285 (94.6%) zerosZeros
Electronics_amt_3m has 32112 (64.2%) zerosZeros
MusicStores_amt_3m has 49307 (98.6%) zerosZeros
Restaurants_amt_3m has 20254 (40.5%) zerosZeros
DigitalGoods_amt_3m has 44043 (88.1%) zerosZeros
Alcohol_amt_3m has 43436 (86.9%) zerosZeros
Books_amt_3m has 45427 (90.9%) zerosZeros
Jewelry_amt_3m has 44421 (88.8%) zerosZeros
DirectM_amt_3m has 47389 (94.8%) zerosZeros
Cash_amt_3m has 50000 (100.0%) zerosZeros
QuasiCash_amt_3m has 49969 (99.9%) zerosZeros
FS_amt_3m has 49931 (99.9%) zerosZeros
RentPayments_amt_3m has 38583 (77.2%) zerosZeros
WalletLoad_amt_3m has 39449 (78.9%) zerosZeros
BusinessServ_amt_3m has 28973 (57.9%) zerosZeros
ProfServ_amt_3m has 44022 (88.0%) zerosZeros
Education_amt_3m has 41554 (83.1%) zerosZeros
GovtServices_amt_3m has 36573 (73.1%) zerosZeros
Agri_6m has 50000 (100.0%) zerosZeros
Contract_6m has 49536 (99.1%) zerosZeros
Airline_6m has 46359 (92.7%) zerosZeros
transport_6m has 37570 (75.1%) zerosZeros
Insurance_6m has 39445 (78.9%) zerosZeros
Hotels_6m has 36891 (73.8%) zerosZeros
Railways_6m has 39278 (78.6%) zerosZeros
Airports_6m has 49945 (99.9%) zerosZeros
Utility_6m has 20688 (41.4%) zerosZeros
Retail_6m has 25725 (51.4%) zerosZeros
Medical_6m has 32314 (64.6%) zerosZeros
Fuel_6m has 21967 (43.9%) zerosZeros
DeptStores_6m has 20359 (40.7%) zerosZeros
Food_6m has 34180 (68.4%) zerosZeros
Auto_6m has 46021 (92.0%) zerosZeros
ClothStores_6m has 24277 (48.6%) zerosZeros
MiscServices_6m has 34785 (69.6%) zerosZeros
HomeF_6m has 47285 (94.6%) zerosZeros
Electronics_6m has 32112 (64.2%) zerosZeros
MusicStores_6m has 49307 (98.6%) zerosZeros
Restaurants_6m has 20254 (40.5%) zerosZeros
DigitalGoods_6m has 44043 (88.1%) zerosZeros
Alcohol_6m has 43436 (86.9%) zerosZeros
Books_6m has 45427 (90.9%) zerosZeros
Jewelry_6m has 44421 (88.8%) zerosZeros
DirectM_6m has 47389 (94.8%) zerosZeros
Cash_6m has 50000 (100.0%) zerosZeros
QuasiCash_6m has 49969 (99.9%) zerosZeros
FS_6m has 49931 (99.9%) zerosZeros
RentPayments_6m has 38583 (77.2%) zerosZeros
WalletLoad_6m has 39449 (78.9%) zerosZeros
BusinessServ_6m has 28973 (57.9%) zerosZeros
ProfServ_6m has 44022 (88.0%) zerosZeros
Education_6m has 41554 (83.1%) zerosZeros
GovtServices_6m has 36573 (73.1%) zerosZeros
Agri_amt_6m has 50000 (100.0%) zerosZeros
Contract_amt_6m has 49536 (99.1%) zerosZeros
Airline_amt_6m has 46359 (92.7%) zerosZeros
transport_amt_6m has 37570 (75.1%) zerosZeros
Insurance_amt_6m has 39445 (78.9%) zerosZeros
Hotels_amt_6m has 36891 (73.8%) zerosZeros
Railways_amt_6m has 39278 (78.6%) zerosZeros
Airports_amt_6m has 49945 (99.9%) zerosZeros
Utility_amt_6m has 20688 (41.4%) zerosZeros
Retail_amt_6m has 25725 (51.4%) zerosZeros
Medical_amt_6m has 32314 (64.6%) zerosZeros
Fuel_amt_6m has 21967 (43.9%) zerosZeros
DeptStores_amt_6m has 20359 (40.7%) zerosZeros
Food_amt_6m has 34180 (68.4%) zerosZeros
Auto_amt_6m has 46021 (92.0%) zerosZeros
ClothStores_amt_6m has 24277 (48.6%) zerosZeros
MiscServices_amt_6m has 34785 (69.6%) zerosZeros
HomeF_amt_6m has 47285 (94.6%) zerosZeros
Electronics_amt_6m has 32112 (64.2%) zerosZeros
MusicStores_amt_6m has 49307 (98.6%) zerosZeros
Restaurants_amt_6m has 20254 (40.5%) zerosZeros
DigitalGoods_amt_6m has 44043 (88.1%) zerosZeros
Alcohol_amt_6m has 43436 (86.9%) zerosZeros
Books_amt_6m has 45427 (90.9%) zerosZeros
Jewelry_amt_6m has 44421 (88.8%) zerosZeros
DirectM_amt_6m has 47389 (94.8%) zerosZeros
Cash_amt_6m has 50000 (100.0%) zerosZeros
QuasiCash_amt_6m has 49969 (99.9%) zerosZeros
FS_amt_6m has 49931 (99.9%) zerosZeros
RentPayments_amt_6m has 38583 (77.2%) zerosZeros
WalletLoad_amt_6m has 39449 (78.9%) zerosZeros
BusinessServ_amt_6m has 28973 (57.9%) zerosZeros
ProfServ_amt_6m has 44022 (88.0%) zerosZeros
Education_amt_6m has 41554 (83.1%) zerosZeros
GovtServices_amt_6m has 36573 (73.1%) zerosZeros
Agri_12m has 50000 (100.0%) zerosZeros
Contract_12m has 49536 (99.1%) zerosZeros
Airline_12m has 46359 (92.7%) zerosZeros
transport_12m has 37570 (75.1%) zerosZeros
Insurance_12m has 39445 (78.9%) zerosZeros
Hotels_12m has 36891 (73.8%) zerosZeros
Railways_12m has 39278 (78.6%) zerosZeros
Airports_12m has 49945 (99.9%) zerosZeros
Utility_12m has 20688 (41.4%) zerosZeros
Retail_12m has 25725 (51.4%) zerosZeros
Medical_12m has 32314 (64.6%) zerosZeros
Fuel_12m has 21967 (43.9%) zerosZeros
DeptStores_12m has 20359 (40.7%) zerosZeros
Food_12m has 34180 (68.4%) zerosZeros
Auto_12m has 46021 (92.0%) zerosZeros
ClothStores_12m has 24277 (48.6%) zerosZeros
MiscServices_12m has 34785 (69.6%) zerosZeros
HomeF_12m has 47285 (94.6%) zerosZeros
Electronics_12m has 32112 (64.2%) zerosZeros
MusicStores_12m has 49307 (98.6%) zerosZeros
Restaurants_12m has 20254 (40.5%) zerosZeros
DigitalGoods_12m has 44043 (88.1%) zerosZeros
Alcohol_12m has 43436 (86.9%) zerosZeros
Books_12m has 45427 (90.9%) zerosZeros
Jewelry_12m has 44421 (88.8%) zerosZeros
DirectM_12m has 47389 (94.8%) zerosZeros
Cash_12m has 50000 (100.0%) zerosZeros
QuasiCash_12m has 49969 (99.9%) zerosZeros
FS_12m has 49931 (99.9%) zerosZeros
RentPayments_12m has 38583 (77.2%) zerosZeros
WalletLoad_12m has 39449 (78.9%) zerosZeros
BusinessServ_12m has 28973 (57.9%) zerosZeros
ProfServ_12m has 44022 (88.0%) zerosZeros
Education_12m has 41554 (83.1%) zerosZeros
GovtServices_12m has 36573 (73.1%) zerosZeros
Agri_amt_12m has 50000 (100.0%) zerosZeros
Contract_amt_12m has 49536 (99.1%) zerosZeros
Airline_amt_12m has 46359 (92.7%) zerosZeros
transport_amt_12m has 37570 (75.1%) zerosZeros
Insurance_amt_12m has 39445 (78.9%) zerosZeros
Hotels_amt_12m has 36891 (73.8%) zerosZeros
Railways_amt_12m has 39278 (78.6%) zerosZeros
Airports_amt_12m has 49945 (99.9%) zerosZeros
Utility_amt_12m has 20688 (41.4%) zerosZeros
Retail_amt_12m has 25725 (51.4%) zerosZeros
Medical_amt_12m has 32314 (64.6%) zerosZeros
Fuel_amt_12m has 21967 (43.9%) zerosZeros
DeptStores_amt_12m has 20359 (40.7%) zerosZeros
Food_amt_12m has 34180 (68.4%) zerosZeros
Auto_amt_12m has 46021 (92.0%) zerosZeros
ClothStores_amt_12m has 24277 (48.6%) zerosZeros
MiscServices_amt_12m has 34785 (69.6%) zerosZeros
HomeF_amt_12m has 47285 (94.6%) zerosZeros
Electronics_amt_12m has 32112 (64.2%) zerosZeros
MusicStores_amt_12m has 49307 (98.6%) zerosZeros
Restaurants_amt_12m has 20254 (40.5%) zerosZeros
DigitalGoods_amt_12m has 44043 (88.1%) zerosZeros
Alcohol_amt_12m has 43436 (86.9%) zerosZeros
Books_amt_12m has 45427 (90.9%) zerosZeros
Jewelry_amt_12m has 44421 (88.8%) zerosZeros
DirectM_amt_12m has 47389 (94.8%) zerosZeros
Cash_amt_12m has 50000 (100.0%) zerosZeros
QuasiCash_amt_12m has 49969 (99.9%) zerosZeros
FS_amt_12m has 49931 (99.9%) zerosZeros
RentPayments_amt_12m has 38583 (77.2%) zerosZeros
WalletLoad_amt_12m has 39449 (78.9%) zerosZeros
BusinessServ_amt_12m has 28973 (57.9%) zerosZeros
ProfServ_amt_12m has 44022 (88.0%) zerosZeros
Education_amt_12m has 41554 (83.1%) zerosZeros
GovtServices_amt_12m has 36573 (73.1%) zerosZeros
revolve_1m has 42442 (84.9%) zerosZeros
revolve_3m has 40062 (80.1%) zerosZeros
revolve_6m has 37978 (76.0%) zerosZeros
util_1m has 3793 (7.6%) zerosZeros
util_3m has 1946 (3.9%) zerosZeros
util_6m has 1531 (3.1%) zerosZeros
payment_ratio_1m has 1703 (3.4%) zerosZeros
married_flag has 50000 (100.0%) zerosZeros
ASSET_OWNERSHIP has 33073 (66.1%) zerosZeros
avg_sa_balance_1m has 2473 (4.9%) zerosZeros
avg_sa_balance_3m has 2366 (4.7%) zerosZeros
avg_sa_balance_6m has 1679 (3.4%) zerosZeros
avg_sa_balance_12m has 988 (2.0%) zerosZeros
pctchg_curr_sa_bal_avg_sa_bal_1m has 757 (1.5%) zerosZeros

Reproduction

Analysis started2023-04-05 17:37:48.375869
Analysis finished2023-04-05 17:37:50.279784
Duration1.9 second
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

transaction_amount
Real number (ℝ)

Distinct22241
Distinct (%)44.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14737.97827
Minimum2500
Maximum730874.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:50.380627image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile2680
Q13650
median5964.28
Q314339.5625
95-th percentile50650
Maximum730874.46
Range728374.46
Interquartile range (IQR)10689.5625

Descriptive statistics

Standard deviation26510.12308
Coefficient of variation (CV)1.79876253
Kurtosis95.2552533
Mean14737.97827
Median Absolute Deviation (MAD)2964.28
Skewness7.263113935
Sum736898913.6
Variance702786625.9
MonotonicityNot monotonic
2023-04-05T23:07:50.582699image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10000 729
 
1.5%
5000 707
 
1.4%
3035.4 528
 
1.1%
3000 511
 
1.0%
4000 438
 
0.9%
20000 396
 
0.8%
5059 349
 
0.7%
2500 332
 
0.7%
2529.5 305
 
0.6%
50000 260
 
0.5%
Other values (22231) 45445
90.9%
ValueCountFrequency (%)
2500 332
0.7%
2500.16 1
 
< 0.1%
2500.34 1
 
< 0.1%
2501 2
 
< 0.1%
2501.05 1
 
< 0.1%
ValueCountFrequency (%)
730874.46 1
< 0.1%
700000 1
< 0.1%
677800 1
< 0.1%
670168 1
< 0.1%
544680 1
< 0.1%

merchant_country
Categorical

HIGH CARDINALITY  IMBALANCE 

Distinct66
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size390.8 KiB
IN
48584 
US
 
383
GB
 
198
AE
 
130
CA
 
107
Other values (61)
 
598

Unique

Unique22 ?
Unique (%)< 0.1%

Sample

1st rowIN
2nd rowIN
3rd rowIN
4th rowIN
5th rowHK

Common Values

ValueCountFrequency (%)
IN 48584
97.2%
US 383
 
0.8%
GB 198
 
0.4%
AE 130
 
0.3%
CA 107
 
0.2%
SG 81
 
0.2%
IE 74
 
0.1%
AU 62
 
0.1%
NG 45
 
0.1%
DE 39
 
0.1%
Other values (56) 297
 
0.6%

target_variable
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0524
Minimum0
Maximum1
Zeros47380
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:50.649537image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.222834542
Coefficient of variation (CV)4.252567595
Kurtosis14.1408011
Mean0.0524
Median Absolute Deviation (MAD)0
Skewness4.017491191
Sum2620
Variance0.0496552331
MonotonicityNot monotonic
2023-04-05T23:07:50.691819image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 47380
94.8%
1 2620
 
5.2%
ValueCountFrequency (%)
0 47380
94.8%
1 2620
 
5.2%
ValueCountFrequency (%)
1 2620
 
5.2%
0 47380
94.8%
Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size390.8 KiB
Fuel
5588 
Cloth stores
5242 
Utility
4660 
Rent Payments
4408 
Dept stores
3881 
Other values (26)
26221 

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowHotels
2nd rowFuel
3rd rowRetail
4th rowRetail
5th rowRetail

Common Values

ValueCountFrequency (%)
Fuel 5588
 
11.2%
Cloth stores 5242
 
10.5%
Utility 4660
 
9.3%
Rent Payments 4408
 
8.8%
Dept stores 3881
 
7.8%
Retail 3135
 
6.3%
Insurance 2384
 
4.8%
Electronics 2200
 
4.4%
Govt services 1935
 
3.9%
Restaurants 1820
 
3.6%
Other values (21) 14747
29.5%

revolve_interest_rate
Real number (ℝ)

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.113156
Minimum9
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:50.740281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile9
Q120
median24
Q334
95-th percentile36
Maximum36
Range27
Interquartile range (IQR)14

Descriptive statistics

Standard deviation8.727472462
Coefficient of variation (CV)0.3475259128
Kurtosis-1.073215156
Mean25.113156
Median Absolute Deviation (MAD)8
Skewness-0.3171745023
Sum1255657.8
Variance76.16877558
MonotonicityNot monotonic
2023-04-05T23:07:50.797864image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
36 7326
14.7%
34 5481
11.0%
24 5100
10.2%
22 4677
9.4%
9 4020
8.0%
20 3810
7.6%
18 3205
 
6.4%
30 3014
 
6.0%
32 2735
 
5.5%
12 2512
 
5.0%
Other values (17) 8120
16.2%
ValueCountFrequency (%)
9 4020
8.0%
10 184
 
0.4%
11 57
 
0.1%
12 2512
5.0%
13 58
 
0.1%
ValueCountFrequency (%)
36 7326
14.7%
35.88 1504
 
3.0%
35 54
 
0.1%
34 5481
11.0%
33 594
 
1.2%

credit_limit
Real number (ℝ)

Distinct1043
Distinct (%)2.1%
Missing62
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean226145.3237
Minimum0
Maximum1500000
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:50.859722image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25000
Q167000
median138000
Q3300000
95-th percentile702000
Maximum1500000
Range1500000
Interquartile range (IQR)233000

Descriptive statistics

Standard deviation257343.3887
Coefficient of variation (CV)1.137955826
Kurtosis9.417986126
Mean226145.3237
Median Absolute Deviation (MAD)87000
Skewness2.78742799
Sum1.129324518 × 1010
Variance6.622561968 × 1010
MonotonicityNot monotonic
2023-04-05T23:07:50.926538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25000 2508
 
5.0%
100000 1751
 
3.5%
400000 1401
 
2.8%
500000 1370
 
2.7%
300000 1177
 
2.4%
65000 1022
 
2.0%
450000 1005
 
2.0%
40000 824
 
1.6%
150000 759
 
1.5%
1500000 732
 
1.5%
Other values (1033) 37389
74.8%
ValueCountFrequency (%)
0 2
 
< 0.1%
25000 2508
5.0%
26000 114
 
0.2%
27000 146
 
0.3%
28000 163
 
0.3%
ValueCountFrequency (%)
1500000 732
1.5%
1495000 1
 
< 0.1%
1494000 3
 
< 0.1%
1486000 1
 
< 0.1%
1479000 1
 
< 0.1%

Agri_1m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:50.983408image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:07:51.024413image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00558
Minimum0
Maximum11
Zeros49798
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.067737image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1063442043
Coefficient of variation (CV)19.05810112
Kurtosis2680.81846
Mean0.00558
Median Absolute Deviation (MAD)0
Skewness37.91046285
Sum279
Variance0.01130908978
MonotonicityNot monotonic
2023-04-05T23:07:51.110647image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 49798
99.6%
1 153
 
0.3%
2 31
 
0.1%
3 16
 
< 0.1%
11 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 49798
99.6%
1 153
 
0.3%
2 31
 
0.1%
3 16
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
5 1
 
< 0.1%
3 16
 
< 0.1%
2 31
 
0.1%
1 153
0.3%

Airline_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09704
Minimum0
Maximum28
Zeros47940
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.157888image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum28
Range28
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8630168795
Coefficient of variation (CV)8.893413845
Kurtosis607.7491246
Mean0.09704
Median Absolute Deviation (MAD)0
Skewness21.70080878
Sum4852
Variance0.7447981344
MonotonicityNot monotonic
2023-04-05T23:07:51.203868image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 47940
95.9%
1 1172
 
2.3%
2 482
 
1.0%
3 142
 
0.3%
4 84
 
0.2%
5 55
 
0.1%
8 28
 
0.1%
6 16
 
< 0.1%
10 16
 
< 0.1%
28 14
 
< 0.1%
Other values (8) 51
 
0.1%
ValueCountFrequency (%)
0 47940
95.9%
1 1172
 
2.3%
2 482
 
1.0%
3 142
 
0.3%
4 84
 
0.2%
ValueCountFrequency (%)
28 14
< 0.1%
27 12
< 0.1%
19 8
< 0.1%
18 4
 
< 0.1%
15 4
 
< 0.1%

transport_1m
Real number (ℝ)

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.48938
Minimum0
Maximum93
Zeros42622
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.261947image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum93
Range93
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.965235753
Coefficient of variation (CV)6.059168238
Kurtosis526.7675517
Mean0.48938
Median Absolute Deviation (MAD)0
Skewness19.45658534
Sum24469
Variance8.792623068
MonotonicityNot monotonic
2023-04-05T23:07:51.324163image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 42622
85.2%
1 3938
 
7.9%
2 1401
 
2.8%
3 629
 
1.3%
4 328
 
0.7%
5 191
 
0.4%
6 153
 
0.3%
7 95
 
0.2%
8 80
 
0.2%
9 69
 
0.1%
Other values (35) 494
 
1.0%
ValueCountFrequency (%)
0 42622
85.2%
1 3938
 
7.9%
2 1401
 
2.8%
3 629
 
1.3%
4 328
 
0.7%
ValueCountFrequency (%)
93 25
0.1%
79 1
 
< 0.1%
62 4
 
< 0.1%
56 2
 
< 0.1%
48 1
 
< 0.1%

Insurance_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2595
Minimum0
Maximum108
Zeros43650
Zeros (%)87.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.383526image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum108
Range108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.647790659
Coefficient of variation (CV)6.349867663
Kurtosis1961.001728
Mean0.2595
Median Absolute Deviation (MAD)0
Skewness35.09705685
Sum12975
Variance2.715214054
MonotonicityNot monotonic
2023-04-05T23:07:51.439864image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 43650
87.3%
1 4242
 
8.5%
2 1194
 
2.4%
3 358
 
0.7%
4 156
 
0.3%
5 78
 
0.2%
9 67
 
0.1%
6 62
 
0.1%
7 48
 
0.1%
8 22
 
< 0.1%
Other values (17) 123
 
0.2%
ValueCountFrequency (%)
0 43650
87.3%
1 4242
 
8.5%
2 1194
 
2.4%
3 358
 
0.7%
4 156
 
0.3%
ValueCountFrequency (%)
108 5
< 0.1%
42 9
< 0.1%
36 7
< 0.1%
31 3
 
< 0.1%
25 2
 
< 0.1%

Hotels_1m
Real number (ℝ)

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3045
Minimum0
Maximum33
Zeros42350
Zeros (%)84.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.492489image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.036436797
Coefficient of variation (CV)3.403733323
Kurtosis157.6047939
Mean0.3045
Median Absolute Deviation (MAD)0
Skewness8.557458357
Sum15225
Variance1.074201234
MonotonicityNot monotonic
2023-04-05T23:07:51.540561image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 42350
84.7%
1 4329
 
8.7%
2 1706
 
3.4%
3 714
 
1.4%
4 335
 
0.7%
5 203
 
0.4%
6 128
 
0.3%
7 87
 
0.2%
8 47
 
0.1%
9 43
 
0.1%
Other values (8) 58
 
0.1%
ValueCountFrequency (%)
0 42350
84.7%
1 4329
 
8.7%
2 1706
 
3.4%
3 714
 
1.4%
4 335
 
0.7%
ValueCountFrequency (%)
33 6
< 0.1%
17 8
< 0.1%
15 7
< 0.1%
14 2
 
< 0.1%
13 3
 
< 0.1%

Railways_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct25
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.35474
Minimum0
Maximum80
Zeros43568
Zeros (%)87.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.593649image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum80
Range80
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.117892642
Coefficient of variation (CV)5.970267356
Kurtosis842.0651933
Mean0.35474
Median Absolute Deviation (MAD)0
Skewness24.6112462
Sum17737
Variance4.485469242
MonotonicityNot monotonic
2023-04-05T23:07:51.648340image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0 43568
87.1%
1 3065
 
6.1%
2 1596
 
3.2%
3 627
 
1.3%
4 421
 
0.8%
5 181
 
0.4%
6 102
 
0.2%
8 85
 
0.2%
7 77
 
0.2%
9 54
 
0.1%
Other values (15) 224
 
0.4%
ValueCountFrequency (%)
0 43568
87.1%
1 3065
 
6.1%
2 1596
 
3.2%
3 627
 
1.3%
4 421
 
0.8%
ValueCountFrequency (%)
80 20
< 0.1%
43 2
 
< 0.1%
41 8
 
< 0.1%
35 5
 
< 0.1%
27 2
 
< 0.1%

Airports_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00068
Minimum0
Maximum4
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.699991image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03032418162
Coefficient of variation (CV)44.59438474
Kurtosis6756.463545
Mean0.00068
Median Absolute Deviation (MAD)0
Skewness67.35704306
Sum34
Variance0.0009195559911
MonotonicityNot monotonic
2023-04-05T23:07:51.806616image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=3)
ValueCountFrequency (%)
0 49969
99.9%
1 30
 
0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
1 30
 
0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
4 1
 
< 0.1%
1 30
 
0.1%
0 49969
99.9%

Utility_1m
Real number (ℝ)

Distinct47
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.45542
Minimum0
Maximum187
Zeros29041
Zeros (%)58.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.865611image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum187
Range187
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.960684794
Coefficient of variation (CV)4.095508372
Kurtosis502.2070453
Mean1.45542
Median Absolute Deviation (MAD)0
Skewness19.60222597
Sum72771
Variance35.52976322
MonotonicityNot monotonic
2023-04-05T23:07:51.926140image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 29041
58.1%
1 8733
 
17.5%
2 4589
 
9.2%
3 2605
 
5.2%
4 1465
 
2.9%
5 1017
 
2.0%
6 727
 
1.5%
7 425
 
0.9%
8 282
 
0.6%
9 177
 
0.4%
Other values (37) 939
 
1.9%
ValueCountFrequency (%)
0 29041
58.1%
1 8733
 
17.5%
2 4589
 
9.2%
3 2605
 
5.2%
4 1465
 
2.9%
ValueCountFrequency (%)
187 19
< 0.1%
125 34
0.1%
115 1
 
< 0.1%
110 4
 
< 0.1%
64 11
 
< 0.1%

Retail_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.83748
Minimum0
Maximum336
Zeros33810
Zeros (%)67.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:51.991975image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum336
Range336
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.120777459
Coefficient of variation (CV)4.920448797
Kurtosis2737.456052
Mean0.83748
Median Absolute Deviation (MAD)0
Skewness42.86004666
Sum41874
Variance16.98080687
MonotonicityNot monotonic
2023-04-05T23:07:52.052529image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 33810
67.6%
1 8416
 
16.8%
2 3575
 
7.1%
3 1745
 
3.5%
4 898
 
1.8%
5 462
 
0.9%
6 297
 
0.6%
7 175
 
0.4%
8 102
 
0.2%
10 88
 
0.2%
Other values (32) 432
 
0.9%
ValueCountFrequency (%)
0 33810
67.6%
1 8416
 
16.8%
2 3575
 
7.1%
3 1745
 
3.5%
4 898
 
1.8%
ValueCountFrequency (%)
336 2
 
< 0.1%
253 2
 
< 0.1%
191 3
< 0.1%
139 5
< 0.1%
78 3
< 0.1%

Medical_1m
Real number (ℝ)

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.58122
Minimum0
Maximum48
Zeros38877
Zeros (%)77.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.112907image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.732588627
Coefficient of variation (CV)2.980951493
Kurtosis83.1243986
Mean0.58122
Median Absolute Deviation (MAD)0
Skewness6.976751922
Sum29061
Variance3.001863349
MonotonicityNot monotonic
2023-04-05T23:07:52.169897image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 38877
77.8%
1 5076
 
10.2%
2 2424
 
4.8%
3 1355
 
2.7%
4 771
 
1.5%
5 471
 
0.9%
6 280
 
0.6%
7 224
 
0.4%
8 140
 
0.3%
9 87
 
0.2%
Other values (20) 295
 
0.6%
ValueCountFrequency (%)
0 38877
77.8%
1 5076
 
10.2%
2 2424
 
4.8%
3 1355
 
2.7%
4 771
 
1.5%
ValueCountFrequency (%)
48 1
 
< 0.1%
35 5
< 0.1%
32 4
< 0.1%
30 4
< 0.1%
27 6
< 0.1%

Fuel_1m
Real number (ℝ)

Distinct37
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4189
Minimum0
Maximum78
Zeros27687
Zeros (%)55.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.227770image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum78
Range78
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.652531528
Coefficient of variation (CV)1.869428098
Kurtosis49.33397331
Mean1.4189
Median Absolute Deviation (MAD)0
Skewness4.782184887
Sum70945
Variance7.035923508
MonotonicityNot monotonic
2023-04-05T23:07:52.361719image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 27687
55.4%
1 7339
 
14.7%
2 5001
 
10.0%
3 3279
 
6.6%
4 2253
 
4.5%
5 1395
 
2.8%
6 872
 
1.7%
7 660
 
1.3%
8 390
 
0.8%
9 249
 
0.5%
Other values (27) 875
 
1.8%
ValueCountFrequency (%)
0 27687
55.4%
1 7339
 
14.7%
2 5001
 
10.0%
3 3279
 
6.6%
4 2253
 
4.5%
ValueCountFrequency (%)
78 1
 
< 0.1%
45 7
< 0.1%
39 1
 
< 0.1%
36 2
 
< 0.1%
35 15
< 0.1%

DeptStores_1m
Real number (ℝ)

Distinct49
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.49474
Minimum0
Maximum73
Zeros27906
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.448933image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum73
Range73
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.276081041
Coefficient of variation (CV)2.191739728
Kurtosis62.29091797
Mean1.49474
Median Absolute Deviation (MAD)0
Skewness5.883793824
Sum74737
Variance10.73270699
MonotonicityNot monotonic
2023-04-05T23:07:52.529058image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 27906
55.8%
1 8640
 
17.3%
2 4540
 
9.1%
3 2647
 
5.3%
4 1744
 
3.5%
5 1056
 
2.1%
6 774
 
1.5%
7 545
 
1.1%
8 438
 
0.9%
9 319
 
0.6%
Other values (39) 1391
 
2.8%
ValueCountFrequency (%)
0 27906
55.8%
1 8640
 
17.3%
2 4540
 
9.1%
3 2647
 
5.3%
4 1744
 
3.5%
ValueCountFrequency (%)
73 3
< 0.1%
64 5
< 0.1%
57 1
 
< 0.1%
52 1
 
< 0.1%
48 5
< 0.1%

Food_1m
Real number (ℝ)

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.36458
Minimum0
Maximum37
Zeros40586
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.598569image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum37
Range37
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.139143264
Coefficient of variation (CV)3.124535806
Kurtosis176.9498114
Mean0.36458
Median Absolute Deviation (MAD)0
Skewness9.087545062
Sum18229
Variance1.297647377
MonotonicityNot monotonic
2023-04-05T23:07:52.658138image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0 40586
81.2%
1 5568
 
11.1%
2 1959
 
3.9%
3 833
 
1.7%
4 424
 
0.8%
5 239
 
0.5%
6 153
 
0.3%
8 73
 
0.1%
7 69
 
0.1%
9 27
 
0.1%
Other values (13) 69
 
0.1%
ValueCountFrequency (%)
0 40586
81.2%
1 5568
 
11.1%
2 1959
 
3.9%
3 833
 
1.7%
4 424
 
0.8%
ValueCountFrequency (%)
37 5
< 0.1%
31 1
 
< 0.1%
29 1
 
< 0.1%
23 6
< 0.1%
22 2
 
< 0.1%

Auto_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07724
Minimum0
Maximum42
Zeros47966
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.724924image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8945445694
Coefficient of variation (CV)11.58136418
Kurtosis1157.133416
Mean0.07724
Median Absolute Deviation (MAD)0
Skewness30.78082838
Sum3862
Variance0.8002099866
MonotonicityNot monotonic
2023-04-05T23:07:52.782337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 47966
95.9%
1 1633
 
3.3%
2 236
 
0.5%
3 50
 
0.1%
22 40
 
0.1%
4 35
 
0.1%
6 11
 
< 0.1%
42 9
 
< 0.1%
9 8
 
< 0.1%
5 8
 
< 0.1%
Other values (2) 4
 
< 0.1%
ValueCountFrequency (%)
0 47966
95.9%
1 1633
 
3.3%
2 236
 
0.5%
3 50
 
0.1%
4 35
 
0.1%
ValueCountFrequency (%)
42 9
 
< 0.1%
22 40
0.1%
9 8
 
< 0.1%
8 3
 
< 0.1%
7 1
 
< 0.1%

ClothStores_1m
Real number (ℝ)

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.89906
Minimum0
Maximum35
Zeros31985
Zeros (%)64.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.842774image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum35
Range35
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.932859497
Coefficient of variation (CV)2.14986708
Kurtosis52.02206417
Mean0.89906
Median Absolute Deviation (MAD)0
Skewness5.301012622
Sum44953
Variance3.735945835
MonotonicityNot monotonic
2023-04-05T23:07:52.904376image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 31985
64.0%
1 8084
 
16.2%
2 4227
 
8.5%
3 2202
 
4.4%
4 1311
 
2.6%
5 782
 
1.6%
6 432
 
0.9%
7 241
 
0.5%
8 222
 
0.4%
9 141
 
0.3%
Other values (17) 373
 
0.7%
ValueCountFrequency (%)
0 31985
64.0%
1 8084
 
16.2%
2 4227
 
8.5%
3 2202
 
4.4%
4 1311
 
2.6%
ValueCountFrequency (%)
35 9
< 0.1%
32 4
 
< 0.1%
29 5
< 0.1%
28 5
< 0.1%
25 11
< 0.1%

MiscServices_1m
Real number (ℝ)

Distinct34
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3543
Minimum0
Maximum54
Zeros41405
Zeros (%)82.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:52.961566image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum54
Range54
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.562056436
Coefficient of variation (CV)4.408852488
Kurtosis422.4997249
Mean0.3543
Median Absolute Deviation (MAD)0
Skewness16.38863338
Sum17715
Variance2.44002031
MonotonicityNot monotonic
2023-04-05T23:07:53.082892image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 41405
82.8%
1 5515
 
11.0%
2 1640
 
3.3%
3 534
 
1.1%
4 284
 
0.6%
5 193
 
0.4%
6 108
 
0.2%
7 59
 
0.1%
8 46
 
0.1%
12 31
 
0.1%
Other values (24) 185
 
0.4%
ValueCountFrequency (%)
0 41405
82.8%
1 5515
 
11.0%
2 1640
 
3.3%
3 534
 
1.1%
4 284
 
0.6%
ValueCountFrequency (%)
54 10
< 0.1%
47 1
 
< 0.1%
43 3
 
< 0.1%
41 1
 
< 0.1%
39 3
 
< 0.1%

HomeF_1m
Real number (ℝ)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0355
Minimum0
Maximum7
Zeros48659
Zeros (%)97.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.130839image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2483565655
Coefficient of variation (CV)6.995959591
Kurtosis156.4066711
Mean0.0355
Median Absolute Deviation (MAD)0
Skewness10.44828341
Sum1775
Variance0.06168098362
MonotonicityNot monotonic
2023-04-05T23:07:53.172854image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 48659
97.3%
1 1056
 
2.1%
2 203
 
0.4%
3 39
 
0.1%
4 27
 
0.1%
5 12
 
< 0.1%
7 4
 
< 0.1%
ValueCountFrequency (%)
0 48659
97.3%
1 1056
 
2.1%
2 203
 
0.4%
3 39
 
0.1%
4 27
 
0.1%
ValueCountFrequency (%)
7 4
 
< 0.1%
5 12
 
< 0.1%
4 27
 
0.1%
3 39
 
0.1%
2 203
0.4%

Electronics_1m
Real number (ℝ)

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51764
Minimum0
Maximum87
Zeros38735
Zeros (%)77.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.227422image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum87
Range87
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.762348135
Coefficient of variation (CV)3.404582595
Kurtosis420.0657876
Mean0.51764
Median Absolute Deviation (MAD)0
Skewness14.41010391
Sum25882
Variance3.105870948
MonotonicityNot monotonic
2023-04-05T23:07:53.280713image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 38735
77.5%
1 6189
 
12.4%
2 2276
 
4.6%
3 1023
 
2.0%
4 587
 
1.2%
5 399
 
0.8%
6 238
 
0.5%
7 188
 
0.4%
8 93
 
0.2%
9 60
 
0.1%
Other values (20) 212
 
0.4%
ValueCountFrequency (%)
0 38735
77.5%
1 6189
 
12.4%
2 2276
 
4.6%
3 1023
 
2.0%
4 587
 
1.2%
ValueCountFrequency (%)
87 2
 
< 0.1%
56 1
 
< 0.1%
46 13
< 0.1%
34 9
< 0.1%
30 9
< 0.1%

MusicStores_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01558
Minimum0
Maximum24
Zeros49582
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.327809image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3019587508
Coefficient of variation (CV)19.38117784
Kurtosis4085.538385
Mean0.01558
Median Absolute Deviation (MAD)0
Skewness55.36205687
Sum779
Variance0.09117908718
MonotonicityNot monotonic
2023-04-05T23:07:53.376388image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 49582
99.2%
1 289
 
0.6%
2 70
 
0.1%
3 21
 
< 0.1%
4 17
 
< 0.1%
5 9
 
< 0.1%
24 5
 
< 0.1%
6 3
 
< 0.1%
10 2
 
< 0.1%
8 2
 
< 0.1%
ValueCountFrequency (%)
0 49582
99.2%
1 289
 
0.6%
2 70
 
0.1%
3 21
 
< 0.1%
4 17
 
< 0.1%
ValueCountFrequency (%)
24 5
< 0.1%
10 2
 
< 0.1%
8 2
 
< 0.1%
6 3
 
< 0.1%
5 9
< 0.1%

Restaurants_1m
Real number (ℝ)

Distinct58
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.89406
Minimum0
Maximum96
Zeros27910
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.434791image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile9
Maximum96
Range96
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.315577505
Coefficient of variation (CV)2.278479829
Kurtosis70.16146989
Mean1.89406
Median Absolute Deviation (MAD)0
Skewness6.135574759
Sum94703
Variance18.6242092
MonotonicityNot monotonic
2023-04-05T23:07:53.501349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27910
55.8%
1 7334
 
14.7%
2 3998
 
8.0%
3 2721
 
5.4%
4 1816
 
3.6%
5 1351
 
2.7%
6 939
 
1.9%
7 716
 
1.4%
8 524
 
1.0%
10 433
 
0.9%
Other values (48) 2258
 
4.5%
ValueCountFrequency (%)
0 27910
55.8%
1 7334
 
14.7%
2 3998
 
8.0%
3 2721
 
5.4%
4 1816
 
3.6%
ValueCountFrequency (%)
96 7
< 0.1%
79 3
< 0.1%
74 1
 
< 0.1%
72 5
< 0.1%
65 1
 
< 0.1%

DigitalGoods_1m
Real number (ℝ)

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.21066
Minimum0
Maximum60
Zeros46387
Zeros (%)92.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.564222image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum60
Range60
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.675547228
Coefficient of variation (CV)7.953798671
Kurtosis478.5131011
Mean0.21066
Median Absolute Deviation (MAD)0
Skewness19.18152645
Sum10533
Variance2.807458514
MonotonicityNot monotonic
2023-04-05T23:07:53.621621image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 46387
92.8%
1 2193
 
4.4%
2 622
 
1.2%
3 199
 
0.4%
4 128
 
0.3%
5 101
 
0.2%
6 54
 
0.1%
7 51
 
0.1%
9 34
 
0.1%
10 33
 
0.1%
Other values (21) 198
 
0.4%
ValueCountFrequency (%)
0 46387
92.8%
1 2193
 
4.4%
2 622
 
1.2%
3 199
 
0.4%
4 128
 
0.3%
ValueCountFrequency (%)
60 2
 
< 0.1%
57 7
 
< 0.1%
45 1
 
< 0.1%
39 26
0.1%
34 8
 
< 0.1%

Alcohol_1m
Real number (ℝ)

Distinct24
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15902
Minimum0
Maximum46
Zeros46220
Zeros (%)92.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.675855image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum46
Range46
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.861897614
Coefficient of variation (CV)5.420057942
Kurtosis598.9823221
Mean0.15902
Median Absolute Deviation (MAD)0
Skewness16.80135382
Sum7951
Variance0.7428674969
MonotonicityNot monotonic
2023-04-05T23:07:53.726072image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 46220
92.4%
1 2162
 
4.3%
2 783
 
1.6%
3 312
 
0.6%
4 198
 
0.4%
5 114
 
0.2%
6 76
 
0.2%
7 39
 
0.1%
8 20
 
< 0.1%
10 15
 
< 0.1%
Other values (14) 61
 
0.1%
ValueCountFrequency (%)
0 46220
92.4%
1 2162
 
4.3%
2 783
 
1.6%
3 312
 
0.6%
4 198
 
0.4%
ValueCountFrequency (%)
46 3
< 0.1%
29 1
 
< 0.1%
24 2
< 0.1%
20 1
 
< 0.1%
19 1
 
< 0.1%

Books_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0702
Minimum0
Maximum24
Zeros47598
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.772614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4855478093
Coefficient of variation (CV)6.91663546
Kurtosis961.3418814
Mean0.0702
Median Absolute Deviation (MAD)0
Skewness24.29408508
Sum3510
Variance0.2357566751
MonotonicityNot monotonic
2023-04-05T23:07:53.822081image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 47598
95.2%
1 1887
 
3.8%
2 331
 
0.7%
3 79
 
0.2%
4 58
 
0.1%
5 13
 
< 0.1%
6 12
 
< 0.1%
24 6
 
< 0.1%
17 6
 
< 0.1%
13 5
 
< 0.1%
Other values (2) 5
 
< 0.1%
ValueCountFrequency (%)
0 47598
95.2%
1 1887
 
3.8%
2 331
 
0.7%
3 79
 
0.2%
4 58
 
0.1%
ValueCountFrequency (%)
24 6
< 0.1%
17 6
< 0.1%
13 5
< 0.1%
10 2
 
< 0.1%
8 3
< 0.1%

Jewelry_1m
Real number (ℝ)

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.06568
Minimum0
Maximum16
Zeros47539
Zeros (%)95.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.869447image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3374735773
Coefficient of variation (CV)5.138148253
Kurtosis246.9610492
Mean0.06568
Median Absolute Deviation (MAD)0
Skewness9.938496392
Sum3284
Variance0.1138884154
MonotonicityNot monotonic
2023-04-05T23:07:53.914156image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 47539
95.1%
1 1868
 
3.7%
2 443
 
0.9%
3 110
 
0.2%
4 28
 
0.1%
5 6
 
< 0.1%
6 2
 
< 0.1%
7 2
 
< 0.1%
16 2
 
< 0.1%
ValueCountFrequency (%)
0 47539
95.1%
1 1868
 
3.7%
2 443
 
0.9%
3 110
 
0.2%
4 28
 
0.1%
ValueCountFrequency (%)
16 2
 
< 0.1%
7 2
 
< 0.1%
6 2
 
< 0.1%
5 6
 
< 0.1%
4 28
0.1%

DirectM_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03162
Minimum0
Maximum16
Zeros48713
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:53.962499image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2486391201
Coefficient of variation (CV)7.863349781
Kurtosis830.2001144
Mean0.03162
Median Absolute Deviation (MAD)0
Skewness20.70773763
Sum1581
Variance0.06182141203
MonotonicityNot monotonic
2023-04-05T23:07:54.007757image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 48713
97.4%
1 1139
 
2.3%
2 98
 
0.2%
3 18
 
< 0.1%
4 15
 
< 0.1%
5 8
 
< 0.1%
8 5
 
< 0.1%
12 3
 
< 0.1%
16 1
 
< 0.1%
ValueCountFrequency (%)
0 48713
97.4%
1 1139
 
2.3%
2 98
 
0.2%
3 18
 
< 0.1%
4 15
 
< 0.1%
ValueCountFrequency (%)
16 1
 
< 0.1%
12 3
 
< 0.1%
8 5
 
< 0.1%
5 8
< 0.1%
4 15
< 0.1%

Cash_1m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.067354image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:07:54.141034image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00052
Minimum0
Maximum3
Zeros49979
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.191206image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum3
Range3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.0282797736
Coefficient of variation (CV)54.38418
Kurtosis6121.55337
Mean0.00052
Median Absolute Deviation (MAD)0
Skewness70.69349454
Sum26
Variance0.0007997455949
MonotonicityNot monotonic
2023-04-05T23:07:54.259216image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49979
> 99.9%
1 18
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 49979
> 99.9%
1 18
 
< 0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
ValueCountFrequency (%)
3 2
 
< 0.1%
2 1
 
< 0.1%
1 18
 
< 0.1%
0 49979
> 99.9%

FS_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00058
Minimum0
Maximum1
Zeros49971
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.307004image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.02407644479
Coefficient of variation (CV)41.5111117
Kurtosis1719.310558
Mean0.00058
Median Absolute Deviation (MAD)0
Skewness41.48785106
Sum29
Variance0.0005796751935
MonotonicityNot monotonic
2023-04-05T23:07:54.355669image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 49971
99.9%
1 29
 
0.1%
ValueCountFrequency (%)
0 49971
99.9%
1 29
 
0.1%
ValueCountFrequency (%)
1 29
 
0.1%
0 49971
99.9%

RentPayments_1m
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22996
Minimum0
Maximum5
Zeros41830
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.399259image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5617514661
Coefficient of variation (CV)2.442822518
Kurtosis5.363768354
Mean0.22996
Median Absolute Deviation (MAD)0
Skewness2.45732873
Sum11498
Variance0.3155647097
MonotonicityNot monotonic
2023-04-05T23:07:54.445261image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 41830
83.7%
1 4945
 
9.9%
2 3151
 
6.3%
3 47
 
0.1%
4 25
 
0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
0 41830
83.7%
1 4945
 
9.9%
2 3151
 
6.3%
3 47
 
0.1%
4 25
 
0.1%
ValueCountFrequency (%)
5 2
 
< 0.1%
4 25
 
0.1%
3 47
 
0.1%
2 3151
6.3%
1 4945
9.9%

WalletLoad_1m
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40908
Minimum0
Maximum86
Zeros43000
Zeros (%)86.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.503971image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.841119591
Coefficient of variation (CV)4.500634572
Kurtosis415.6964358
Mean0.40908
Median Absolute Deviation (MAD)0
Skewness14.618551
Sum20454
Variance3.389721348
MonotonicityNot monotonic
2023-04-05T23:07:54.631662image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 43000
86.0%
1 3260
 
6.5%
2 1427
 
2.9%
3 771
 
1.5%
4 421
 
0.8%
5 318
 
0.6%
6 197
 
0.4%
7 131
 
0.3%
8 100
 
0.2%
11 70
 
0.1%
Other values (32) 305
 
0.6%
ValueCountFrequency (%)
0 43000
86.0%
1 3260
 
6.5%
2 1427
 
2.9%
3 771
 
1.5%
4 421
 
0.8%
ValueCountFrequency (%)
86 2
< 0.1%
73 1
< 0.1%
67 1
< 0.1%
63 2
< 0.1%
56 1
< 0.1%

BusinessServ_1m
Real number (ℝ)

Distinct37
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60752
Minimum0
Maximum89
Zeros36948
Zeros (%)73.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.690362image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum89
Range89
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.407229807
Coefficient of variation (CV)3.962387752
Kurtosis392.7975466
Mean0.60752
Median Absolute Deviation (MAD)0
Skewness16.14891128
Sum30376
Variance5.794755345
MonotonicityNot monotonic
2023-04-05T23:07:54.745366image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 36948
73.9%
1 7457
 
14.9%
2 2855
 
5.7%
3 1159
 
2.3%
4 572
 
1.1%
5 279
 
0.6%
6 180
 
0.4%
7 112
 
0.2%
8 82
 
0.2%
9 49
 
0.1%
Other values (27) 307
 
0.6%
ValueCountFrequency (%)
0 36948
73.9%
1 7457
 
14.9%
2 2855
 
5.7%
3 1159
 
2.3%
4 572
 
1.1%
ValueCountFrequency (%)
89 5
 
< 0.1%
74 4
 
< 0.1%
52 11
< 0.1%
48 14
< 0.1%
39 16
< 0.1%

ProfServ_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.10514
Minimum0
Maximum42
Zeros47143
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.798473image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9035606835
Coefficient of variation (CV)8.593881335
Kurtosis1026.527155
Mean0.10514
Median Absolute Deviation (MAD)0
Skewness27.49568756
Sum5257
Variance0.8164219088
MonotonicityNot monotonic
2023-04-05T23:07:54.846909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 47143
94.3%
1 2109
 
4.2%
2 476
 
1.0%
3 101
 
0.2%
4 53
 
0.1%
20 34
 
0.1%
5 15
 
< 0.1%
8 15
 
< 0.1%
6 11
 
< 0.1%
42 9
 
< 0.1%
Other values (9) 34
 
0.1%
ValueCountFrequency (%)
0 47143
94.3%
1 2109
 
4.2%
2 476
 
1.0%
3 101
 
0.2%
4 53
 
0.1%
ValueCountFrequency (%)
42 9
 
< 0.1%
29 1
 
< 0.1%
20 34
0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%

Education_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct22
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.20048
Minimum0
Maximum62
Zeros44712
Zeros (%)89.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:54.897719image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum62
Range62
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.332502638
Coefficient of variation (CV)6.646561444
Kurtosis1188.321691
Mean0.20048
Median Absolute Deviation (MAD)0
Skewness29.11196446
Sum10024
Variance1.775563281
MonotonicityNot monotonic
2023-04-05T23:07:54.947616image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 44712
89.4%
1 3569
 
7.1%
2 1099
 
2.2%
3 266
 
0.5%
4 128
 
0.3%
5 61
 
0.1%
7 27
 
0.1%
23 26
 
0.1%
6 24
 
< 0.1%
8 17
 
< 0.1%
Other values (12) 71
 
0.1%
ValueCountFrequency (%)
0 44712
89.4%
1 3569
 
7.1%
2 1099
 
2.2%
3 266
 
0.5%
4 128
 
0.3%
ValueCountFrequency (%)
62 12
< 0.1%
27 7
 
< 0.1%
23 26
0.1%
20 3
 
< 0.1%
19 5
 
< 0.1%

GovtServices_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct32
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.60268
Minimum0
Maximum388
Zeros41869
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.006249image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum388
Range388
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.196283245
Coefficient of variation (CV)11.9404713
Kurtosis1502.741409
Mean0.60268
Median Absolute Deviation (MAD)0
Skewness35.99012688
Sum30134
Variance51.78649255
MonotonicityNot monotonic
2023-04-05T23:07:55.072844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 41869
83.7%
1 4228
 
8.5%
2 1753
 
3.5%
3 765
 
1.5%
4 478
 
1.0%
5 262
 
0.5%
6 127
 
0.3%
7 121
 
0.2%
9 49
 
0.1%
8 47
 
0.1%
Other values (22) 301
 
0.6%
ValueCountFrequency (%)
0 41869
83.7%
1 4228
 
8.5%
2 1753
 
3.5%
3 765
 
1.5%
4 478
 
1.0%
ValueCountFrequency (%)
388 6
 
< 0.1%
212 33
0.1%
128 2
 
< 0.1%
66 5
 
< 0.1%
63 10
 
< 0.1%

Agri_amt_1m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.131210image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:07:55.173047image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct111
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean112.435134
Minimum0
Maximum440000
Zeros49798
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.232254image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum440000
Range440000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4112.885925
Coefficient of variation (CV)36.58007759
Kurtosis5464.972954
Mean112.435134
Median Absolute Deviation (MAD)0
Skewness64.54806412
Sum5621756.7
Variance16915830.63
MonotonicityNot monotonic
2023-04-05T23:07:55.296349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49798
99.6%
1155 6
 
< 0.1%
199 6
 
< 0.1%
100000 5
 
< 0.1%
5000 5
 
< 0.1%
409 4
 
< 0.1%
82620 4
 
< 0.1%
4000 4
 
< 0.1%
8084 4
 
< 0.1%
80000 4
 
< 0.1%
Other values (101) 160
 
0.3%
ValueCountFrequency (%)
0 49798
99.6%
100 1
 
< 0.1%
105 1
 
< 0.1%
160 1
 
< 0.1%
177 1
 
< 0.1%
ValueCountFrequency (%)
440000 1
< 0.1%
400000 1
< 0.1%
300000 1
< 0.1%
240200 1
< 0.1%
149000 1
< 0.1%

Airline_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct828
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1940.360609
Minimum0
Maximum1126000
Zeros47940
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.364653image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1126000
Range1126000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22353.52351
Coefficient of variation (CV)11.5202934
Kurtosis791.933801
Mean1940.360609
Median Absolute Deviation (MAD)0
Skewness23.81293327
Sum97018030.43
Variance499680013.2
MonotonicityNot monotonic
2023-04-05T23:07:55.428799image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47940
95.9%
200 38
 
0.1%
150 36
 
0.1%
170811 33
 
0.1%
250 30
 
0.1%
300 22
 
< 0.1%
450 22
 
< 0.1%
180561 20
 
< 0.1%
1000 18
 
< 0.1%
1900 16
 
< 0.1%
Other values (818) 1825
 
3.6%
ValueCountFrequency (%)
0 47940
95.9%
50 2
 
< 0.1%
99 3
 
< 0.1%
100 14
 
< 0.1%
150 36
 
0.1%
ValueCountFrequency (%)
1126000 2
 
< 0.1%
951246 2
 
< 0.1%
795029.67 8
< 0.1%
763930 1
 
< 0.1%
579881 2
 
< 0.1%

transport_amt_1m
Real number (ℝ)

Distinct3598
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2854.610835
Minimum0
Maximum1019060
Zeros42622
Zeros (%)85.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.496898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9149.98
Maximum1019060
Range1019060
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22211.82309
Coefficient of variation (CV)7.781033693
Kurtosis477.8016997
Mean2854.610835
Median Absolute Deviation (MAD)0
Skewness18.87638663
Sum142730541.8
Variance493365085
MonotonicityNot monotonic
2023-04-05T23:07:55.571950image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42622
85.2%
2 129
 
0.3%
1000 99
 
0.2%
500 58
 
0.1%
2000 52
 
0.1%
1 40
 
0.1%
1500 34
 
0.1%
200 32
 
0.1%
3000 29
 
0.1%
100 28
 
0.1%
Other values (3588) 6877
 
13.8%
ValueCountFrequency (%)
0 42622
85.2%
1 40
 
0.1%
2 129
 
0.3%
2.8 1
 
< 0.1%
3 5
 
< 0.1%
ValueCountFrequency (%)
1019060 1
 
< 0.1%
621273.75 25
0.1%
554867.5 1
 
< 0.1%
485167.3 5
 
< 0.1%
469000 1
 
< 0.1%

Insurance_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct3821
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4530.527613
Minimum0
Maximum1499400
Zeros43650
Zeros (%)87.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.700717image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile21383
Maximum1499400
Range1499400
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31811.01473
Coefficient of variation (CV)7.02148126
Kurtosis875.5214758
Mean4530.527613
Median Absolute Deviation (MAD)0
Skewness24.36113882
Sum226526380.6
Variance1011940658
MonotonicityNot monotonic
2023-04-05T23:07:55.765465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43650
87.3%
301502 33
 
0.1%
5000 31
 
0.1%
10000 27
 
0.1%
52250 25
 
0.1%
887 20
 
< 0.1%
102250 17
 
< 0.1%
100000 14
 
< 0.1%
189.15 14
 
< 0.1%
3801 14
 
< 0.1%
Other values (3811) 6155
 
12.3%
ValueCountFrequency (%)
0 43650
87.3%
1 1
 
< 0.1%
2 2
 
< 0.1%
31 2
 
< 0.1%
60 1
 
< 0.1%
ValueCountFrequency (%)
1499400 1
 
< 0.1%
1424909 5
< 0.1%
1270273.52 2
 
< 0.1%
1187200.8 4
< 0.1%
1025000 1
 
< 0.1%

Hotels_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct3524
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2884.816496
Minimum0
Maximum1907180
Zeros42350
Zeros (%)84.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.837661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10000
Maximum1907180
Range1907180
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26387.0404
Coefficient of variation (CV)9.146869632
Kurtosis2065.809682
Mean2884.816496
Median Absolute Deviation (MAD)0
Skewness37.30334908
Sum144240824.8
Variance696275901.2
MonotonicityNot monotonic
2023-04-05T23:07:55.907078image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 42350
84.7%
3000 45
 
0.1%
5000 33
 
0.1%
4000 31
 
0.1%
10000 28
 
0.1%
2000 27
 
0.1%
500 24
 
< 0.1%
1000 23
 
< 0.1%
1500 21
 
< 0.1%
4907.22 20
 
< 0.1%
Other values (3514) 7398
 
14.8%
ValueCountFrequency (%)
0 42350
84.7%
1 1
 
< 0.1%
2 10
 
< 0.1%
4 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
1907180 2
 
< 0.1%
1619913.87 2
 
< 0.1%
1059961.12 7
< 0.1%
727800 2
 
< 0.1%
500255 1
 
< 0.1%

Railways_amt_1m
Real number (ℝ)

Distinct3705
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2692.439748
Minimum0
Maximum528866.72
Zeros43568
Zeros (%)87.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:55.979407image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10846
Maximum528866.72
Range528866.72
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19035.23855
Coefficient of variation (CV)7.069884687
Kurtosis370.8320888
Mean2692.439748
Median Absolute Deviation (MAD)0
Skewness16.92727723
Sum134621987.4
Variance362340306.5
MonotonicityNot monotonic
2023-04-05T23:07:56.046580image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43568
87.1%
500 26
 
0.1%
39747.7 25
 
0.1%
200 23
 
< 0.1%
528866.72 20
 
< 0.1%
100 20
 
< 0.1%
300 15
 
< 0.1%
36000 14
 
< 0.1%
102.12 12
 
< 0.1%
478.28 12
 
< 0.1%
Other values (3695) 6265
 
12.5%
ValueCountFrequency (%)
0 43568
87.1%
10 1
 
< 0.1%
10.18 4
 
< 0.1%
12.46 1
 
< 0.1%
15.32 1
 
< 0.1%
ValueCountFrequency (%)
528866.72 20
< 0.1%
464415 4
 
< 0.1%
450000 2
 
< 0.1%
438045 2
 
< 0.1%
360731 10
< 0.1%

Airports_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0220772
Minimum0
Maximum5200
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.114766image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5200
Range5200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation94.19555942
Coefficient of variation (CV)46.5835624
Kurtosis2562.249108
Mean2.0220772
Median Absolute Deviation (MAD)0
Skewness50.09701966
Sum101103.86
Variance8872.803414
MonotonicityNot monotonic
2023-04-05T23:07:56.208449image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 49969
99.9%
4800 12
 
< 0.1%
750 3
 
< 0.1%
600 3
 
< 0.1%
5200 3
 
< 0.1%
1920 2
 
< 0.1%
3350.93 2
 
< 0.1%
5015 2
 
< 0.1%
150 1
 
< 0.1%
1032 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
150 1
 
< 0.1%
600 3
 
< 0.1%
750 3
 
< 0.1%
900 1
 
< 0.1%
ValueCountFrequency (%)
5200 3
 
< 0.1%
5015 2
 
< 0.1%
4800 12
< 0.1%
3350.93 2
 
< 0.1%
1920 2
 
< 0.1%

Utility_amt_1m
Real number (ℝ)

Distinct9121
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8443.610838
Minimum0
Maximum1254359.37
Zeros29041
Zeros (%)58.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.275180image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32185.5
95-th percentile30219.1135
Maximum1254359.37
Range1254359.37
Interquartile range (IQR)2185.5

Descriptive statistics

Standard deviation49511.556
Coefficient of variation (CV)5.863789431
Kurtosis354.4779543
Mean8443.610838
Median Absolute Deviation (MAD)0
Skewness16.41213199
Sum422180541.9
Variance2451394177
MonotonicityNot monotonic
2023-04-05T23:07:56.350337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29041
58.1%
649 321
 
0.6%
199 199
 
0.4%
1178.82 191
 
0.4%
470.82 152
 
0.3%
2 109
 
0.2%
499 107
 
0.2%
4000 97
 
0.2%
666 90
 
0.2%
179 81
 
0.2%
Other values (9111) 19612
39.2%
ValueCountFrequency (%)
0 29041
58.1%
1 7
 
< 0.1%
1.18 1
 
< 0.1%
2 109
 
0.2%
4 8
 
< 0.1%
ValueCountFrequency (%)
1254359.37 34
0.1%
1084581.17 6
 
< 0.1%
1081000 2
 
< 0.1%
1004000 5
 
< 0.1%
981095.4 3
 
< 0.1%

Retail_amt_1m
Real number (ℝ)

Distinct6892
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5016.588801
Minimum0
Maximum1181801.25
Zeros33810
Zeros (%)67.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.418812image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31129
95-th percentile19422.8
Maximum1181801.25
Range1181801.25
Interquartile range (IQR)1129

Descriptive statistics

Standard deviation27788.98853
Coefficient of variation (CV)5.539419241
Kurtosis307.0039721
Mean5016.588801
Median Absolute Deviation (MAD)0
Skewness14.66204411
Sum250829440.1
Variance772227883.6
MonotonicityNot monotonic
2023-04-05T23:07:56.488049image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33810
67.6%
4000 139
 
0.3%
5000 98
 
0.2%
10000 84
 
0.2%
1000 82
 
0.2%
500 72
 
0.1%
2000 67
 
0.1%
3000 62
 
0.1%
20000 41
 
0.1%
300 41
 
0.1%
Other values (6882) 15504
31.0%
ValueCountFrequency (%)
0 33810
67.6%
1 5
 
< 0.1%
2 32
 
0.1%
4 2
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
1181801.25 1
 
< 0.1%
770777.19 1
 
< 0.1%
739538.3 2
 
< 0.1%
725899 11
< 0.1%
700000 1
 
< 0.1%

Medical_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4713
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2680.438368
Minimum0
Maximum1000000
Zeros38877
Zeros (%)77.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.564287image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9201
Maximum1000000
Range1000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation19904.54887
Coefficient of variation (CV)7.425855825
Kurtosis791.0314578
Mean2680.438368
Median Absolute Deviation (MAD)0
Skewness23.06243138
Sum134021918.4
Variance396191065.7
MonotonicityNot monotonic
2023-04-05T23:07:56.642008image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38877
77.8%
1000 60
 
0.1%
1 59
 
0.1%
600 57
 
0.1%
1200 53
 
0.1%
700 50
 
0.1%
500 49
 
0.1%
800 49
 
0.1%
10000 48
 
0.1%
2000 43
 
0.1%
Other values (4703) 10655
 
21.3%
ValueCountFrequency (%)
0 38877
77.8%
1 59
 
0.1%
1.74 1
 
< 0.1%
2 8
 
< 0.1%
2.09 1
 
< 0.1%
ValueCountFrequency (%)
1000000 3
< 0.1%
839527 2
< 0.1%
641090 3
< 0.1%
640000 2
< 0.1%
627682 3
< 0.1%

Fuel_amt_1m
Real number (ℝ)

Distinct10483
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3385.910146
Minimum0
Maximum209341.42
Zeros27687
Zeros (%)55.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.781864image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33541.3
95-th percentile15520.74
Maximum209341.42
Range209341.42
Interquartile range (IQR)3541.3

Descriptive statistics

Standard deviation8724.61551
Coefficient of variation (CV)2.576741595
Kurtosis93.98430096
Mean3385.910146
Median Absolute Deviation (MAD)0
Skewness7.443950529
Sum169295507.3
Variance76118915.8
MonotonicityNot monotonic
2023-04-05T23:07:56.844468image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27687
55.4%
3035.4 330
 
0.7%
2023.6 308
 
0.6%
1011.8 249
 
0.5%
1010 242
 
0.5%
2020 240
 
0.5%
4047.2 167
 
0.3%
2529.5 158
 
0.3%
15177 143
 
0.3%
505 140
 
0.3%
Other values (10473) 20336
40.7%
ValueCountFrequency (%)
0 27687
55.4%
41.36 2
 
< 0.1%
50.5 1
 
< 0.1%
60.71 2
 
< 0.1%
91.06 1
 
< 0.1%
ValueCountFrequency (%)
209341.42 3
< 0.1%
191533.74 2
< 0.1%
179290.96 3
< 0.1%
173523.7 2
< 0.1%
158587.52 1
 
< 0.1%

DeptStores_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct11350
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5049.597079
Minimum0
Maximum1938149.5
Zeros27906
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:56.910797image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32542.71
95-th percentile13212.324
Maximum1938149.5
Range1938149.5
Interquartile range (IQR)2542.71

Descriptive statistics

Standard deviation30571.93462
Coefficient of variation (CV)6.054331494
Kurtosis1107.850284
Mean5049.597079
Median Absolute Deviation (MAD)0
Skewness24.24559308
Sum252479853.9
Variance934643186.7
MonotonicityNot monotonic
2023-04-05T23:07:56.980164image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27906
55.8%
3000 52
 
0.1%
5000 39
 
0.1%
10000 38
 
0.1%
2000 35
 
0.1%
10287 33
 
0.1%
1500 31
 
0.1%
20000 29
 
0.1%
40000 29
 
0.1%
100000 28
 
0.1%
Other values (11340) 21780
43.6%
ValueCountFrequency (%)
0 27906
55.8%
1 4
 
< 0.1%
1.05 1
 
< 0.1%
1.69 1
 
< 0.1%
1.7 1
 
< 0.1%
ValueCountFrequency (%)
1938149.5 3
 
< 0.1%
817900 1
 
< 0.1%
759935.5 8
< 0.1%
727475.8 4
< 0.1%
546292.69 4
< 0.1%

Food_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2944
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean632.4781872
Minimum0
Maximum425795
Zeros40586
Zeros (%)81.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.053108image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2233
Maximum425795
Range425795
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6412.566294
Coefficient of variation (CV)10.13879439
Kurtosis1797.498967
Mean632.4781872
Median Absolute Deviation (MAD)0
Skewness35.66319458
Sum31623909.36
Variance41121006.47
MonotonicityNot monotonic
2023-04-05T23:07:57.118808image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 40586
81.2%
2 68
 
0.1%
500 68
 
0.1%
1000 39
 
0.1%
200 37
 
0.1%
280 37
 
0.1%
3000 35
 
0.1%
290 35
 
0.1%
400 35
 
0.1%
450 34
 
0.1%
Other values (2934) 9026
 
18.1%
ValueCountFrequency (%)
0 40586
81.2%
1 1
 
< 0.1%
2 68
 
0.1%
4 8
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
425795 3
< 0.1%
368838 1
 
< 0.1%
300000 2
< 0.1%
215400 1
 
< 0.1%
211000 3
< 0.1%

Auto_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct981
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1125.258359
Minimum0
Maximum800000
Zeros47966
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.184596image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum800000
Range800000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17153.09059
Coefficient of variation (CV)15.24369088
Kurtosis980.4680534
Mean1125.258359
Median Absolute Deviation (MAD)0
Skewness28.59649908
Sum56262917.96
Variance294228516.8
MonotonicityNot monotonic
2023-04-05T23:07:57.252349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47966
95.9%
405478.09 33
 
0.1%
10000 33
 
0.1%
3000 26
 
0.1%
21000 19
 
< 0.1%
2500 15
 
< 0.1%
1200 13
 
< 0.1%
3800 12
 
< 0.1%
20000 12
 
< 0.1%
6500 12
 
< 0.1%
Other values (971) 1859
 
3.7%
ValueCountFrequency (%)
0 47966
95.9%
59 2
 
< 0.1%
66 1
 
< 0.1%
84 1
 
< 0.1%
100 1
 
< 0.1%
ValueCountFrequency (%)
800000 4
 
< 0.1%
709100 4
 
< 0.1%
619991 4
 
< 0.1%
405478.09 33
0.1%
364000 1
 
< 0.1%

ClothStores_amt_1m
Real number (ℝ)

Distinct7935
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4652.230616
Minimum0
Maximum603800
Zeros31985
Zeros (%)64.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.328771image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33056
95-th percentile21521.05
Maximum603800
Range603800
Interquartile range (IQR)3056

Descriptive statistics

Standard deviation16866.19586
Coefficient of variation (CV)3.625399782
Kurtosis241.5658057
Mean4652.230616
Median Absolute Deviation (MAD)0
Skewness11.93664938
Sum232611530.8
Variance284468562.9
MonotonicityNot monotonic
2023-04-05T23:07:57.396483image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 31985
64.0%
3000 54
 
0.1%
5000 49
 
0.1%
699 48
 
0.1%
400 43
 
0.1%
1000 40
 
0.1%
2999 38
 
0.1%
999 34
 
0.1%
3150 33
 
0.1%
2000 33
 
0.1%
Other values (7925) 17643
35.3%
ValueCountFrequency (%)
0 31985
64.0%
1 4
 
< 0.1%
2 14
 
< 0.1%
3.1 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
603800 3
 
< 0.1%
599000 1
 
< 0.1%
374660 1
 
< 0.1%
364011 9
< 0.1%
330000 1
 
< 0.1%

MiscServices_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct3091
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1180.529477
Minimum0
Maximum449080
Zeros41405
Zeros (%)82.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.479584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4900
Maximum449080
Range449080
Interquartile range (IQR)0

Descriptive statistics

Standard deviation8592.298051
Coefficient of variation (CV)7.27834266
Kurtosis838.4218734
Mean1180.529477
Median Absolute Deviation (MAD)0
Skewness23.69752565
Sum59026473.83
Variance73827585.8
MonotonicityNot monotonic
2023-04-05T23:07:57.586997image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41405
82.8%
2 389
 
0.8%
500 58
 
0.1%
600 55
 
0.1%
1000 54
 
0.1%
5000 54
 
0.1%
199 50
 
0.1%
10000 45
 
0.1%
2500 44
 
0.1%
3000 43
 
0.1%
Other values (3081) 7803
 
15.6%
ValueCountFrequency (%)
0 41405
82.8%
1 4
 
< 0.1%
1.01 1
 
< 0.1%
2 389
 
0.8%
3 1
 
< 0.1%
ValueCountFrequency (%)
449080 3
< 0.1%
340665.7 2
< 0.1%
305500 2
< 0.1%
264000 3
< 0.1%
258000 2
< 0.1%

HomeF_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct628
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean493.2986082
Minimum0
Maximum500000
Zeros48659
Zeros (%)97.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.660087image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum500000
Range500000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7444.247378
Coefficient of variation (CV)15.09075285
Kurtosis2643.744869
Mean493.2986082
Median Absolute Deviation (MAD)0
Skewness44.04943211
Sum24664930.41
Variance55416819.02
MonotonicityNot monotonic
2023-04-05T23:07:57.792029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48659
97.3%
5000 26
 
0.1%
15000 11
 
< 0.1%
3494.03 11
 
< 0.1%
13050 9
 
< 0.1%
2000 9
 
< 0.1%
4200 9
 
< 0.1%
14871 8
 
< 0.1%
25000 8
 
< 0.1%
12670 8
 
< 0.1%
Other values (618) 1242
 
2.5%
ValueCountFrequency (%)
0 48659
97.3%
1 1
 
< 0.1%
90 1
 
< 0.1%
92 1
 
< 0.1%
116 1
 
< 0.1%
ValueCountFrequency (%)
500000 6
< 0.1%
345172 1
 
< 0.1%
264700 1
 
< 0.1%
254630 1
 
< 0.1%
203800 1
 
< 0.1%

Electronics_amt_1m
Real number (ℝ)

Distinct5144
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3638.247164
Minimum0
Maximum703690
Zeros38735
Zeros (%)77.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.858716image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile16449.64
Maximum703690
Range703690
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20981.03527
Coefficient of variation (CV)5.766797671
Kurtosis311.8931869
Mean3638.247164
Median Absolute Deviation (MAD)0
Skewness14.98094777
Sum181912358.2
Variance440203841.2
MonotonicityNot monotonic
2023-04-05T23:07:57.924466image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38735
77.5%
1499 54
 
0.1%
2000 45
 
0.1%
10000 40
 
0.1%
5000 38
 
0.1%
299 36
 
0.1%
18840.76 34
 
0.1%
999 29
 
0.1%
2999 29
 
0.1%
399 28
 
0.1%
Other values (5134) 10932
 
21.9%
ValueCountFrequency (%)
0 38735
77.5%
0.57 1
 
< 0.1%
1 14
 
< 0.1%
2 2
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
703690 3
 
< 0.1%
540264 13
< 0.1%
513473.54 2
 
< 0.1%
442395 4
 
< 0.1%
439959 3
 
< 0.1%

MusicStores_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct139
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.7988864
Minimum0
Maximum84846
Zeros49582
Zeros (%)99.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:57.996743image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum84846
Range84846
Interquartile range (IQR)0

Descriptive statistics

Standard deviation986.7304697
Coefficient of variation (CV)32.03786192
Kurtosis5572.01065
Mean30.7988864
Median Absolute Deviation (MAD)0
Skewness68.34431396
Sum1539944.32
Variance973637.0198
MonotonicityNot monotonic
2023-04-05T23:07:58.065289image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49582
99.2%
99 25
 
0.1%
5000 17
 
< 0.1%
2000 15
 
< 0.1%
75 14
 
< 0.1%
449 13
 
< 0.1%
269 11
 
< 0.1%
149 10
 
< 0.1%
169 9
 
< 0.1%
195 9
 
< 0.1%
Other values (129) 295
 
0.6%
ValueCountFrequency (%)
0 49582
99.2%
5 3
 
< 0.1%
15 5
 
< 0.1%
18 6
 
< 0.1%
47 1
 
< 0.1%
ValueCountFrequency (%)
84846 5
< 0.1%
39000 1
 
< 0.1%
26568 1
 
< 0.1%
21000 3
< 0.1%
20246.27 1
 
< 0.1%

Restaurants_amt_1m
Real number (ℝ)

Distinct9381
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2390.744822
Minimum0
Maximum398000
Zeros27910
Zeros (%)55.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:58.134645image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31541
95-th percentile10500.5
Maximum398000
Range398000
Interquartile range (IQR)1541

Descriptive statistics

Standard deviation9801.232451
Coefficient of variation (CV)4.09965646
Kurtosis366.5901605
Mean2390.744822
Median Absolute Deviation (MAD)0
Skewness15.74752972
Sum119537241.1
Variance96064157.56
MonotonicityNot monotonic
2023-04-05T23:07:58.205135image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 27910
55.8%
2 400
 
0.8%
4 69
 
0.1%
1000 54
 
0.1%
300 52
 
0.1%
315 44
 
0.1%
500 33
 
0.1%
220 33
 
0.1%
240 33
 
0.1%
700 31
 
0.1%
Other values (9371) 21341
42.7%
ValueCountFrequency (%)
0 27910
55.8%
1 4
 
< 0.1%
2 400
 
0.8%
3 1
 
< 0.1%
4 69
 
0.1%
ValueCountFrequency (%)
398000 1
 
< 0.1%
375000 1
 
< 0.1%
300000 1
 
< 0.1%
270843 5
< 0.1%
252209 1
 
< 0.1%

DigitalGoods_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1019
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1176.057311
Minimum0
Maximum884000
Zeros46387
Zeros (%)92.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:58.280086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile210
Maximum884000
Range884000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20145.42446
Coefficient of variation (CV)17.12962819
Kurtosis1255.537034
Mean1176.057311
Median Absolute Deviation (MAD)0
Skewness32.85823397
Sum58802865.53
Variance405838126.8
MonotonicityNot monotonic
2023-04-05T23:07:58.346376image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46387
92.8%
130 188
 
0.4%
129 144
 
0.3%
189 122
 
0.2%
2 109
 
0.2%
1300 70
 
0.1%
99 63
 
0.1%
200 57
 
0.1%
299 48
 
0.1%
20 42
 
0.1%
Other values (1009) 2770
 
5.5%
ValueCountFrequency (%)
0 46387
92.8%
1 13
 
< 0.1%
2 109
 
0.2%
3 2
 
< 0.1%
4 12
 
< 0.1%
ValueCountFrequency (%)
884000 2
 
< 0.1%
815000 20
< 0.1%
410196.3 8
 
< 0.1%
306375.49 2
 
< 0.1%
247049.73 7
 
< 0.1%

Alcohol_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1167
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean332.2385978
Minimum0
Maximum200000
Zeros46220
Zeros (%)92.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:58.444695image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1140
Maximum200000
Range200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3051.799615
Coefficient of variation (CV)9.185566142
Kurtosis1863.538122
Mean332.2385978
Median Absolute Deviation (MAD)0
Skewness35.180207
Sum16611929.89
Variance9313480.891
MonotonicityNot monotonic
2023-04-05T23:07:58.558850image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46220
92.4%
360 37
 
0.1%
480 30
 
0.1%
600 28
 
0.1%
540 27
 
0.1%
720 27
 
0.1%
1200 24
 
< 0.1%
900 22
 
< 0.1%
510 21
 
< 0.1%
3000 20
 
< 0.1%
Other values (1157) 3544
 
7.1%
ValueCountFrequency (%)
0 46220
92.4%
90 2
 
< 0.1%
100 1
 
< 0.1%
110 1
 
< 0.1%
115 2
 
< 0.1%
ValueCountFrequency (%)
200000 2
< 0.1%
199994 2
< 0.1%
150750 1
< 0.1%
141800 1
< 0.1%
104000 1
< 0.1%

Books_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1104
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean300.435107
Minimum0
Maximum309000
Zeros47598
Zeros (%)95.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:58.637965image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum309000
Range309000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4717.216042
Coefficient of variation (CV)15.70128102
Kurtosis2036.081226
Mean300.435107
Median Absolute Deviation (MAD)0
Skewness40.21348698
Sum15021755.35
Variance22252127.19
MonotonicityNot monotonic
2023-04-05T23:07:58.704103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47598
95.2%
40000 20
 
< 0.1%
450 17
 
< 0.1%
160 13
 
< 0.1%
300 13
 
< 0.1%
400 13
 
< 0.1%
250 12
 
< 0.1%
1500 12
 
< 0.1%
73600 11
 
< 0.1%
4745.65 11
 
< 0.1%
Other values (1094) 2280
 
4.6%
ValueCountFrequency (%)
0 47598
95.2%
1 1
 
< 0.1%
1.51 1
 
< 0.1%
10 5
 
< 0.1%
14 1
 
< 0.1%
ValueCountFrequency (%)
309000 2
 
< 0.1%
265843.26 4
< 0.1%
250000 1
 
< 0.1%
178387 3
< 0.1%
159630 6
< 0.1%

Jewelry_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1029
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1714.155457
Minimum0
Maximum1126230
Zeros47539
Zeros (%)95.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:58.851675image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1126230
Range1126230
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16593.554
Coefficient of variation (CV)9.680308707
Kurtosis808.8877932
Mean1714.155457
Median Absolute Deviation (MAD)0
Skewness22.24473852
Sum85707772.85
Variance275346034.2
MonotonicityNot monotonic
2023-04-05T23:07:58.925144image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47539
95.1%
10000 99
 
0.2%
5000 66
 
0.1%
2000 51
 
0.1%
3000 37
 
0.1%
20000 34
 
0.1%
6000 26
 
0.1%
15000 21
 
< 0.1%
30000 20
 
< 0.1%
25000 19
 
< 0.1%
Other values (1019) 2088
 
4.2%
ValueCountFrequency (%)
0 47539
95.1%
10 2
 
< 0.1%
110 1
 
< 0.1%
119 3
 
< 0.1%
143 1
 
< 0.1%
ValueCountFrequency (%)
1126230 1
 
< 0.1%
700000 1
 
< 0.1%
600000 3
< 0.1%
500000 1
 
< 0.1%
468000 3
< 0.1%

DirectM_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct418
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.1287112
Minimum0
Maximum1068694.49
Zeros48713
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.000952image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1068694.49
Range1068694.49
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9061.686157
Coefficient of variation (CV)41.73416821
Kurtosis11699.2307
Mean217.1287112
Median Absolute Deviation (MAD)0
Skewness102.1207067
Sum10856435.56
Variance82114156
MonotonicityNot monotonic
2023-04-05T23:07:59.076444image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 48713
97.4%
649 219
 
0.4%
199 187
 
0.4%
499 95
 
0.2%
149 57
 
0.1%
2 20
 
< 0.1%
3584 10
 
< 0.1%
651 8
 
< 0.1%
77.69 7
 
< 0.1%
22600 6
 
< 0.1%
Other values (408) 678
 
1.4%
ValueCountFrequency (%)
0 48713
97.4%
2 20
 
< 0.1%
49 4
 
< 0.1%
50 1
 
< 0.1%
77.69 7
 
< 0.1%
ValueCountFrequency (%)
1068694.49 3
< 0.1%
297027.88 1
 
< 0.1%
276491.33 1
 
< 0.1%
276317.3 1
 
< 0.1%
272880.25 2
< 0.1%

Cash_amt_1m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.135175image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:07:59.180701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.7022194
Minimum0
Maximum149644.47
Zeros49979
Zeros (%)> 99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.231283image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum149644.47
Range149644.47
Interquartile range (IQR)0

Descriptive statistics

Standard deviation967.1283533
Coefficient of variation (CV)111.1358274
Kurtosis22946.11794
Mean8.7022194
Median Absolute Deviation (MAD)0
Skewness149.0971175
Sum435110.97
Variance935337.2518
MonotonicityNot monotonic
2023-04-05T23:07:59.280054image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 49979
> 99.9%
3393.16 4
 
< 0.1%
4457.23 4
 
< 0.1%
5007.12 3
 
< 0.1%
149644.47 2
 
< 0.1%
21072.71 2
 
< 0.1%
8469.32 1
 
< 0.1%
3018.83 1
 
< 0.1%
5013.32 1
 
< 0.1%
27988.24 1
 
< 0.1%
Other values (2) 2
 
< 0.1%
ValueCountFrequency (%)
0 49979
> 99.9%
754.41 1
 
< 0.1%
2009.57 1
 
< 0.1%
3018.83 1
 
< 0.1%
3393.16 4
 
< 0.1%
ValueCountFrequency (%)
149644.47 2
< 0.1%
27988.24 1
< 0.1%
21072.71 2
< 0.1%
8469.32 1
< 0.1%
5013.32 1
< 0.1%

FS_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.116
Minimum0
Maximum200
Zeros49971
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.333496image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum200
Range200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.815288957
Coefficient of variation (CV)41.5111117
Kurtosis1719.310558
Mean0.116
Median Absolute Deviation (MAD)0
Skewness41.48785106
Sum5800
Variance23.18700774
MonotonicityNot monotonic
2023-04-05T23:07:59.380001image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 49971
99.9%
200 29
 
0.1%
ValueCountFrequency (%)
0 49971
99.9%
200 29
 
0.1%
ValueCountFrequency (%)
200 29
 
0.1%
0 49971
99.9%

RentPayments_amt_1m
Real number (ℝ)

Distinct3041
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6477.520894
Minimum0
Maximum1013828
Zeros41830
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.460209image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile47470
Maximum1013828
Range1013828
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22066.68076
Coefficient of variation (CV)3.40665528
Kurtosis139.3584426
Mean6477.520894
Median Absolute Deviation (MAD)0
Skewness7.357924783
Sum323876044.7
Variance486938399.6
MonotonicityNot monotonic
2023-04-05T23:07:59.550279image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41830
83.7%
20300 131
 
0.3%
10150 118
 
0.2%
30420 81
 
0.2%
25375 70
 
0.1%
5097.5 67
 
0.1%
15225 52
 
0.1%
40600 47
 
0.1%
30300 44
 
0.1%
20200 43
 
0.1%
Other values (3031) 7517
 
15.0%
ValueCountFrequency (%)
0 41830
83.7%
10.2 1
 
< 0.1%
30 1
 
< 0.1%
40 1
 
< 0.1%
50 4
 
< 0.1%
ValueCountFrequency (%)
1013828 1
< 0.1%
650914.87 1
< 0.1%
404000 1
< 0.1%
399960 1
< 0.1%
398950 2
< 0.1%

WalletLoad_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2441
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1502.734164
Minimum0
Maximum676919.1
Zeros43000
Zeros (%)86.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.646748image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10000
Maximum676919.1
Range676919.1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7989.728842
Coefficient of variation (CV)5.316794568
Kurtosis2119.799693
Mean1502.734164
Median Absolute Deviation (MAD)0
Skewness29.75791273
Sum75136708.22
Variance63835766.97
MonotonicityNot monotonic
2023-04-05T23:07:59.715523image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43000
86.0%
10230 107
 
0.2%
4000 104
 
0.2%
1000 104
 
0.2%
1023 93
 
0.2%
10430 88
 
0.2%
5115 84
 
0.2%
500 82
 
0.2%
20460 80
 
0.2%
2000 76
 
0.2%
Other values (2431) 6182
 
12.4%
ValueCountFrequency (%)
0 43000
86.0%
1 2
 
< 0.1%
1.02 4
 
< 0.1%
2 22
 
< 0.1%
3.06 1
 
< 0.1%
ValueCountFrequency (%)
676919.1 2
 
< 0.1%
280149.8 1
 
< 0.1%
143220 1
 
< 0.1%
141175.34 2
 
< 0.1%
139762 7
< 0.1%

BusinessServ_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5707
Distinct (%)11.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4310.405115
Minimum0
Maximum3150002
Zeros36948
Zeros (%)73.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.788744image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3203.65
95-th percentile8171.915
Maximum3150002
Range3150002
Interquartile range (IQR)203.65

Descriptive statistics

Standard deviation55370.9265
Coefficient of variation (CV)12.84587528
Kurtosis2318.990171
Mean4310.405115
Median Absolute Deviation (MAD)0
Skewness42.98173804
Sum215520255.8
Variance3065939502
MonotonicityNot monotonic
2023-04-05T23:07:59.867101image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36948
73.9%
1000 66
 
0.1%
1499 56
 
0.1%
5000 46
 
0.1%
899 46
 
0.1%
500 45
 
0.1%
400 44
 
0.1%
600 44
 
0.1%
99 37
 
0.1%
1500 35
 
0.1%
Other values (5697) 12633
 
25.3%
ValueCountFrequency (%)
0 36948
73.9%
1 12
 
< 0.1%
2 34
 
0.1%
4 4
 
< 0.1%
10 6
 
< 0.1%
ValueCountFrequency (%)
3150002 11
< 0.1%
820861.95 1
 
< 0.1%
815000 14
< 0.1%
700898.68 6
< 0.1%
688000 13
< 0.1%

ProfServ_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1059
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1118.518774
Minimum0
Maximum1200000
Zeros47143
Zeros (%)94.3%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:07:59.944739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile800
Maximum1200000
Range1200000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16841.95019
Coefficient of variation (CV)15.05736924
Kurtosis1756.225813
Mean1118.518774
Median Absolute Deviation (MAD)0
Skewness36.72967912
Sum55925938.72
Variance283651286.2
MonotonicityNot monotonic
2023-04-05T23:08:00.028629image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47143
94.3%
1500 46
 
0.1%
1000 46
 
0.1%
3000 42
 
0.1%
5000 35
 
0.1%
265703.89 34
 
0.1%
10000 34
 
0.1%
500 29
 
0.1%
2500 25
 
0.1%
600 23
 
< 0.1%
Other values (1049) 2543
 
5.1%
ValueCountFrequency (%)
0 47143
94.3%
1 2
 
< 0.1%
10 2
 
< 0.1%
29 1
 
< 0.1%
40 1
 
< 0.1%
ValueCountFrequency (%)
1200000 1
 
< 0.1%
1000000 1
 
< 0.1%
900000 1
 
< 0.1%
750000 6
< 0.1%
739668 3
< 0.1%

Education_amt_1m
Real number (ℝ)

Distinct2387
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3479.155835
Minimum0
Maximum750000
Zeros44712
Zeros (%)89.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.194369image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile15263.56
Maximum750000
Range750000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation22623.1084
Coefficient of variation (CV)6.502470563
Kurtosis311.5787156
Mean3479.155835
Median Absolute Deviation (MAD)0
Skewness14.84393027
Sum173957791.7
Variance511805033.8
MonotonicityNot monotonic
2023-04-05T23:08:00.259304image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44712
89.4%
2 359
 
0.7%
10000 42
 
0.1%
68215.44 33
 
0.1%
455 31
 
0.1%
20000 30
 
0.1%
2000 27
 
0.1%
500 27
 
0.1%
15000 24
 
< 0.1%
5000 22
 
< 0.1%
Other values (2377) 4693
 
9.4%
ValueCountFrequency (%)
0 44712
89.4%
1.03 1
 
< 0.1%
2 359
 
0.7%
4 6
 
< 0.1%
10 2
 
< 0.1%
ValueCountFrequency (%)
750000 5
< 0.1%
557790 9
< 0.1%
512631.09 1
 
< 0.1%
507754 6
< 0.1%
486649 3
 
< 0.1%

GovtServices_amt_1m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4121
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8867.47297
Minimum0
Maximum7498137.78
Zeros41869
Zeros (%)83.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.331605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10838.399
Maximum7498137.78
Range7498137.78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation196067.7281
Coefficient of variation (CV)22.11089098
Kurtosis1404.662761
Mean8867.47297
Median Absolute Deviation (MAD)0
Skewness37.02388523
Sum443373648.5
Variance3.8442554 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:00.417016image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41869
83.7%
50 89
 
0.2%
1526.55 50
 
0.1%
201.76 49
 
0.1%
504.4 47
 
0.1%
50445 47
 
0.1%
500 42
 
0.1%
2000 41
 
0.1%
200 33
 
0.1%
7498137.78 33
 
0.1%
Other values (4111) 7700
 
15.4%
ValueCountFrequency (%)
0 41869
83.7%
5.06 2
 
< 0.1%
8.26 5
 
< 0.1%
10 7
 
< 0.1%
10.09 1
 
< 0.1%
ValueCountFrequency (%)
7498137.78 33
0.1%
2417136 5
 
< 0.1%
1050000 1
 
< 0.1%
940491.33 3
 
< 0.1%
918041 6
 
< 0.1%

Agri_3m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.545744image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:00.589530image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01372
Minimum0
Maximum17
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.636617image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1941456037
Coefficient of variation (CV)14.15055421
Kurtosis2097.9857
Mean0.01372
Median Absolute Deviation (MAD)0
Skewness34.78914986
Sum686
Variance0.03769251545
MonotonicityNot monotonic
2023-04-05T23:08:00.681557image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
6 3
 
< 0.1%
5 3
 
< 0.1%
9 2
 
< 0.1%
7 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
14 1
 
< 0.1%
9 2
< 0.1%
7 1
 
< 0.1%
6 3
< 0.1%

Airline_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22376
Minimum0
Maximum86
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.741054image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.227013842
Coefficient of variation (CV)9.952689678
Kurtosis1033.304052
Mean0.22376
Median Absolute Deviation (MAD)0
Skewness29.50974303
Sum11188
Variance4.959590654
MonotonicityNot monotonic
2023-04-05T23:08:00.795159image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
5 107
 
0.2%
6 59
 
0.1%
7 49
 
0.1%
10 38
 
0.1%
8 34
 
0.1%
Other values (20) 146
 
0.3%
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
ValueCountFrequency (%)
86 12
< 0.1%
80 14
< 0.1%
47 8
< 0.1%
38 2
 
< 0.1%
37 1
 
< 0.1%

transport_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.10542
Minimum0
Maximum199
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:00.862351image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum199
Range199
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.996150907
Coefficient of variation (CV)5.424319179
Kurtosis627.6198803
Mean1.10542
Median Absolute Deviation (MAD)0
Skewness21.19144641
Sum55271
Variance35.9538257
MonotonicityNot monotonic
2023-04-05T23:08:00.931549image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
5 448
 
0.9%
6 330
 
0.7%
7 249
 
0.5%
8 198
 
0.4%
9 136
 
0.3%
Other values (63) 1140
 
2.3%
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
ValueCountFrequency (%)
199 25
0.1%
148 1
 
< 0.1%
122 1
 
< 0.1%
120 2
 
< 0.1%
106 1
 
< 0.1%

Insurance_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57774
Minimum0
Maximum348
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.003661image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum348
Range348
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.488919636
Coefficient of variation (CV)7.769792011
Kurtosis3666.095835
Mean0.57774
Median Absolute Deviation (MAD)0
Skewness51.17353581
Sum28887
Variance20.1503995
MonotonicityNot monotonic
2023-04-05T23:08:01.067331image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
5 177
 
0.4%
6 119
 
0.2%
7 78
 
0.2%
12 42
 
0.1%
34 40
 
0.1%
Other values (36) 369
 
0.7%
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
ValueCountFrequency (%)
348 5
< 0.1%
94 9
< 0.1%
91 7
< 0.1%
89 3
 
< 0.1%
73 2
 
< 0.1%

Hotels_3m
Real number (ℝ)

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72448
Minimum0
Maximum65
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.132531image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum65
Range65
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.03482961
Coefficient of variation (CV)2.808676029
Kurtosis156.4901343
Mean0.72448
Median Absolute Deviation (MAD)0
Skewness8.30915014
Sum36224
Variance4.14053154
MonotonicityNot monotonic
2023-04-05T23:08:01.189914image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
5 569
 
1.1%
6 395
 
0.8%
7 281
 
0.6%
8 222
 
0.4%
10 119
 
0.2%
Other values (23) 452
 
0.9%
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
ValueCountFrequency (%)
65 6
< 0.1%
38 3
< 0.1%
36 1
 
< 0.1%
31 2
 
< 0.1%
29 3
< 0.1%

Railways_3m
Real number (ℝ)

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72686
Minimum0
Maximum88
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.259605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum88
Range88
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.135737744
Coefficient of variation (CV)4.314087642
Kurtosis341.1364602
Mean0.72686
Median Absolute Deviation (MAD)0
Skewness15.25758491
Sum36343
Variance9.832851197
MonotonicityNot monotonic
2023-04-05T23:08:01.333599image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
5 388
 
0.8%
6 313
 
0.6%
7 208
 
0.4%
8 180
 
0.4%
10 155
 
0.3%
Other values (35) 627
 
1.3%
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
ValueCountFrequency (%)
88 20
< 0.1%
80 1
 
< 0.1%
67 10
< 0.1%
65 2
 
< 0.1%
61 4
 
< 0.1%

Airports_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00146
Minimum0
Maximum5
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.386587image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04917231699
Coefficient of variation (CV)33.67966917
Kurtosis3033.124738
Mean0.00146
Median Absolute Deviation (MAD)0
Skewness46.50959616
Sum73
Variance0.002417916758
MonotonicityNot monotonic
2023-04-05T23:08:01.502958image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
2 14
 
< 0.1%
1 40
 
0.1%
0 49945
99.9%

Utility_3m
Real number (ℝ)

Distinct90
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5979
Minimum0
Maximum389
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.559541image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile13
Maximum389
Range389
Interquartile range (IQR)4

Descriptive statistics

Standard deviation13.89091627
Coefficient of variation (CV)3.860840009
Kurtosis489.6128409
Mean3.5979
Median Absolute Deviation (MAD)1
Skewness19.79756961
Sum179895
Variance192.9575547
MonotonicityNot monotonic
2023-04-05T23:08:01.633543image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
5 2048
 
4.1%
6 1642
 
3.3%
7 1255
 
2.5%
8 891
 
1.8%
9 832
 
1.7%
Other values (80) 4042
 
8.1%
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
ValueCountFrequency (%)
389 34
0.1%
285 19
< 0.1%
274 1
 
< 0.1%
269 4
 
< 0.1%
176 14
< 0.1%

Retail_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct71
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.84948
Minimum0
Maximum1044
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.706397image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum1044
Range1044
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.256715263
Coefficient of variation (CV)5.005036693
Kurtosis4258.902872
Mean1.84948
Median Absolute Deviation (MAD)0
Skewness52.81860742
Sum92474
Variance85.68677747
MonotonicityNot monotonic
2023-04-05T23:08:01.773756image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
5 1258
 
2.5%
6 838
 
1.7%
7 675
 
1.4%
8 441
 
0.9%
9 401
 
0.8%
Other values (61) 1420
 
2.8%
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
ValueCountFrequency (%)
1044 1
 
< 0.1%
470 2
 
< 0.1%
465 3
< 0.1%
378 2
 
< 0.1%
369 5
< 0.1%

Medical_3m
Real number (ℝ)

Distinct52
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.43778
Minimum0
Maximum83
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.842591image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum83
Range83
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.608189165
Coefficient of variation (CV)2.509555819
Kurtosis71.74185192
Mean1.43778
Median Absolute Deviation (MAD)0
Skewness6.334131441
Sum71889
Variance13.01902905
MonotonicityNot monotonic
2023-04-05T23:08:01.906898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
5 1018
 
2.0%
6 752
 
1.5%
7 616
 
1.2%
8 470
 
0.9%
9 318
 
0.6%
Other values (42) 1617
 
3.2%
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
ValueCountFrequency (%)
83 4
< 0.1%
65 3
 
< 0.1%
61 8
< 0.1%
58 4
< 0.1%
54 5
< 0.1%

Fuel_3m
Real number (ℝ)

Distinct77
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.47412
Minimum0
Maximum193
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:01.971707image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile14
Maximum193
Range193
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.213805795
Coefficient of variation (CV)1.788598492
Kurtosis65.06113242
Mean3.47412
Median Absolute Deviation (MAD)1
Skewness5.34325986
Sum173706
Variance38.61138245
MonotonicityNot monotonic
2023-04-05T23:08:02.047565image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
5 2121
 
4.2%
6 1802
 
3.6%
7 1399
 
2.8%
8 1208
 
2.4%
9 1095
 
2.2%
Other values (67) 5362
 
10.7%
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
ValueCountFrequency (%)
193 1
 
< 0.1%
138 3
< 0.1%
112 1
 
< 0.1%
110 4
< 0.1%
96 1
 
< 0.1%

DeptStores_3m
Real number (ℝ)

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.76012
Minimum0
Maximum187
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.133810image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile16
Maximum187
Range187
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.832164735
Coefficient of variation (CV)2.082956059
Kurtosis65.82871473
Mean3.76012
Median Absolute Deviation (MAD)1
Skewness6.028340139
Sum188006
Variance61.34280444
MonotonicityNot monotonic
2023-04-05T23:08:02.262062image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
5 1889
 
3.8%
6 1340
 
2.7%
7 1108
 
2.2%
8 943
 
1.9%
9 814
 
1.6%
Other values (82) 5430
 
10.9%
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
ValueCountFrequency (%)
187 3
< 0.1%
140 5
< 0.1%
139 1
 
< 0.1%
133 1
 
< 0.1%
124 2
 
< 0.1%

Food_3m
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91748
Minimum0
Maximum114
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.341111image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum114
Range114
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.608962741
Coefficient of variation (CV)2.843618107
Kurtosis433.8072451
Mean0.91748
Median Absolute Deviation (MAD)0
Skewness13.85156464
Sum45874
Variance6.806686583
MonotonicityNot monotonic
2023-04-05T23:08:02.404123image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
5 723
 
1.4%
6 470
 
0.9%
7 316
 
0.6%
8 220
 
0.4%
9 194
 
0.4%
Other values (32) 618
 
1.2%
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
ValueCountFrequency (%)
114 5
< 0.1%
80 1
 
< 0.1%
68 1
 
< 0.1%
56 2
 
< 0.1%
55 2
 
< 0.1%

Auto_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15662
Minimum0
Maximum57
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.458082image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum57
Range57
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.435385447
Coefficient of variation (CV)9.1647647
Kurtosis970.2156726
Mean0.15662
Median Absolute Deviation (MAD)0
Skewness28.46302955
Sum7831
Variance2.060331382
MonotonicityNot monotonic
2023-04-05T23:08:02.507109image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
5 36
 
0.1%
33 33
 
0.1%
6 25
 
0.1%
57 16
 
< 0.1%
12 12
 
< 0.1%
Other values (9) 42
 
0.1%
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
ValueCountFrequency (%)
57 16
< 0.1%
33 33
0.1%
17 4
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%

ClothStores_3m
Real number (ℝ)

Distinct41
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.89714
Minimum0
Maximum59
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.568596image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile8
Maximum59
Range59
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.372338547
Coefficient of variation (CV)1.777590766
Kurtosis34.01497166
Mean1.89714
Median Absolute Deviation (MAD)1
Skewness4.244303483
Sum94857
Variance11.37266727
MonotonicityNot monotonic
2023-04-05T23:08:02.700269image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
5 1730
 
3.5%
6 1223
 
2.4%
7 878
 
1.8%
8 622
 
1.2%
9 504
 
1.0%
Other values (31) 1742
 
3.5%
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
ValueCountFrequency (%)
59 1
 
< 0.1%
57 9
< 0.1%
45 11
< 0.1%
42 1
 
< 0.1%
38 2
 
< 0.1%

MiscServices_3m
Real number (ℝ)

Distinct58
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90552
Minimum0
Maximum93
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.767754image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.282427306
Coefficient of variation (CV)3.624908677
Kurtosis177.2661933
Mean0.90552
Median Absolute Deviation (MAD)0
Skewness11.07163845
Sum45276
Variance10.77432902
MonotonicityNot monotonic
2023-04-05T23:08:02.832696image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
5 456
 
0.9%
6 334
 
0.7%
7 222
 
0.4%
8 139
 
0.3%
9 101
 
0.2%
Other values (48) 721
 
1.4%
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
ValueCountFrequency (%)
93 3
 
< 0.1%
78 1
 
< 0.1%
77 3
 
< 0.1%
66 10
< 0.1%
65 6
< 0.1%

HomeF_3m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07982
Minimum0
Maximum23
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.888252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4301307567
Coefficient of variation (CV)5.388759167
Kurtosis451.2791605
Mean0.07982
Median Absolute Deviation (MAD)0
Skewness13.94272501
Sum3991
Variance0.1850124678
MonotonicityNot monotonic
2023-04-05T23:08:02.937918image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
5 39
 
0.1%
7 6
 
< 0.1%
6 5
 
< 0.1%
8 3
 
< 0.1%
10 2
 
< 0.1%
Other values (3) 4
 
< 0.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
17 2
< 0.1%
10 2
< 0.1%
8 3
< 0.1%

Electronics_3m
Real number (ℝ)

Distinct51
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.28572
Minimum0
Maximum133
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:02.999728image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum133
Range133
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.000290505
Coefficient of variation (CV)3.111323232
Kurtosis328.1721715
Mean1.28572
Median Absolute Deviation (MAD)0
Skewness13.51461061
Sum64286
Variance16.00232413
MonotonicityNot monotonic
2023-04-05T23:08:03.079801image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
5 826
 
1.7%
6 600
 
1.2%
7 412
 
0.8%
8 389
 
0.8%
9 274
 
0.5%
Other values (41) 1331
 
2.7%
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
ValueCountFrequency (%)
133 9
< 0.1%
131 1
 
< 0.1%
87 2
 
< 0.1%
85 4
 
< 0.1%
82 13
< 0.1%

MusicStores_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04938
Minimum0
Maximum163
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:03.144537image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum163
Range163
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.715948864
Coefficient of variation (CV)34.74987575
Kurtosis8177.573029
Mean0.04938
Median Absolute Deviation (MAD)0
Skewness87.28925641
Sum2469
Variance2.944480505
MonotonicityNot monotonic
2023-04-05T23:08:03.267280image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
5 25
 
0.1%
9 9
 
< 0.1%
6 9
 
< 0.1%
14 8
 
< 0.1%
24 6
 
< 0.1%
Other values (8) 18
 
< 0.1%
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
ValueCountFrequency (%)
163 5
< 0.1%
65 1
 
< 0.1%
24 6
< 0.1%
17 2
 
< 0.1%
15 1
 
< 0.1%

Restaurants_3m
Real number (ℝ)

Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9884
Minimum0
Maximum211
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:03.469816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile22
Maximum211
Range211
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.36514226
Coefficient of variation (CV)2.077849063
Kurtosis43.35942087
Mean4.9884
Median Absolute Deviation (MAD)1
Skewness5.114187663
Sum249420
Variance107.4361742
MonotonicityNot monotonic
2023-04-05T23:08:03.781101image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
5 1787
 
3.6%
6 1459
 
2.9%
7 1278
 
2.6%
8 1090
 
2.2%
9 908
 
1.8%
Other values (106) 7539
 
15.1%
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
ValueCountFrequency (%)
211 1
 
< 0.1%
201 1
 
< 0.1%
196 3
< 0.1%
161 1
 
< 0.1%
150 5
< 0.1%

DigitalGoods_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56234
Minimum0
Maximum184
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:04.021890image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum184
Range184
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.329892456
Coefficient of variation (CV)7.699776748
Kurtosis697.1504599
Mean0.56234
Median Absolute Deviation (MAD)0
Skewness22.67581288
Sum28117
Variance18.74796868
MonotonicityNot monotonic
2023-04-05T23:08:04.227905image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
5 213
 
0.4%
6 126
 
0.3%
7 119
 
0.2%
9 111
 
0.2%
10 69
 
0.1%
Other values (43) 517
 
1.0%
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
ValueCountFrequency (%)
184 5
< 0.1%
137 7
< 0.1%
128 8
< 0.1%
121 6
< 0.1%
80 6
< 0.1%

Alcohol_3m
Real number (ℝ)

Distinct44
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40314
Minimum0
Maximum105
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:04.323624image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum105
Range105
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.003411693
Coefficient of variation (CV)4.969518513
Kurtosis661.1060958
Mean0.40314
Median Absolute Deviation (MAD)0
Skewness18.19384547
Sum20157
Variance4.013658414
MonotonicityNot monotonic
2023-04-05T23:08:04.486090image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
5 234
 
0.5%
6 183
 
0.4%
7 129
 
0.3%
8 102
 
0.2%
10 62
 
0.1%
Other values (34) 364
 
0.7%
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
ValueCountFrequency (%)
105 3
< 0.1%
91 1
 
< 0.1%
78 1
 
< 0.1%
50 1
 
< 0.1%
47 2
< 0.1%

Books_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15562
Minimum0
Maximum102
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:04.557127image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum102
Range102
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.165654147
Coefficient of variation (CV)7.490387785
Kurtosis4749.355926
Mean0.15562
Median Absolute Deviation (MAD)0
Skewness57.77552351
Sum7781
Variance1.358749591
MonotonicityNot monotonic
2023-04-05T23:08:04.620477image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
5 46
 
0.1%
7 31
 
0.1%
6 23
 
< 0.1%
8 9
 
< 0.1%
24 6
 
< 0.1%
Other values (9) 27
 
0.1%
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
ValueCountFrequency (%)
102 4
< 0.1%
34 2
 
< 0.1%
27 6
< 0.1%
24 6
< 0.1%
15 4
< 0.1%

Jewelry_3m
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18356
Minimum0
Maximum44
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:04.756910image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum44
Range44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7054329728
Coefficient of variation (CV)3.84306479
Kurtosis636.7629954
Mean0.18356
Median Absolute Deviation (MAD)0
Skewness14.29820106
Sum9178
Variance0.4976356791
MonotonicityNot monotonic
2023-04-05T23:08:05.055664image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
5 74
 
0.1%
6 41
 
0.1%
7 12
 
< 0.1%
8 11
 
< 0.1%
9 9
 
< 0.1%
Other values (4) 17
 
< 0.1%
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
ValueCountFrequency (%)
44 2
 
< 0.1%
14 4
< 0.1%
11 2
 
< 0.1%
10 9
< 0.1%
9 9
< 0.1%

DirectM_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07514
Minimum0
Maximum35
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:05.201923image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4828857463
Coefficient of variation (CV)6.42648052
Kurtosis920.1343764
Mean0.07514
Median Absolute Deviation (MAD)0
Skewness21.74502737
Sum3757
Variance0.233178644
MonotonicityNot monotonic
2023-04-05T23:08:05.373912image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
7 18
 
< 0.1%
5 15
 
< 0.1%
6 13
 
< 0.1%
12 10
 
< 0.1%
14 5
 
< 0.1%
Other values (4) 10
 
< 0.1%
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
ValueCountFrequency (%)
35 1
 
< 0.1%
19 4
 
< 0.1%
14 5
< 0.1%
12 10
< 0.1%
11 1
 
< 0.1%

Cash_3m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:05.547712image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:05.740805image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00088
Minimum0
Maximum5
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:05.858766image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04426358306
Coefficient of variation (CV)50.2995262
Kurtosis7567.308021
Mean0.00088
Median Absolute Deviation (MAD)0
Skewness77.89338677
Sum44
Variance0.001959264785
MonotonicityNot monotonic
2023-04-05T23:08:05.941309image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
1 26
 
0.1%
0 49969
99.9%

FS_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00138
Minimum0
Maximum1
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:05.989282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03712308126
Coefficient of variation (CV)26.90078352
Kurtosis719.7111522
Mean0.00138
Median Absolute Deviation (MAD)0
Skewness26.86414644
Sum69
Variance0.001378123162
MonotonicityNot monotonic
2023-04-05T23:08:06.035983image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
1 69
 
0.1%
0 49931
99.9%

RentPayments_3m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62926
Minimum0
Maximum13
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:06.084317image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.428710144
Coefficient of variation (CV)2.27046077
Kurtosis8.04876218
Mean0.62926
Median Absolute Deviation (MAD)0
Skewness2.738019177
Sum31463
Variance2.041212677
MonotonicityNot monotonic
2023-04-05T23:08:06.144802image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
5 733
 
1.5%
6 428
 
0.9%
7 325
 
0.7%
8 130
 
0.3%
9 64
 
0.1%
Other values (3) 21
 
< 0.1%
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
ValueCountFrequency (%)
13 1
 
< 0.1%
11 2
 
< 0.1%
10 18
 
< 0.1%
9 64
0.1%
8 130
0.3%

WalletLoad_3m
Real number (ℝ)

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9795
Minimum0
Maximum225
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:06.264921image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum225
Range225
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.473615989
Coefficient of variation (CV)4.567244501
Kurtosis569.5985459
Mean0.9795
Median Absolute Deviation (MAD)0
Skewness17.61054299
Sum48975
Variance20.01324001
MonotonicityNot monotonic
2023-04-05T23:08:06.330273image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
5 548
 
1.1%
6 411
 
0.8%
7 266
 
0.5%
9 223
 
0.4%
8 213
 
0.4%
Other values (63) 1105
 
2.2%
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
ValueCountFrequency (%)
225 2
< 0.1%
202 1
< 0.1%
184 1
< 0.1%
162 1
< 0.1%
144 2
< 0.1%

BusinessServ_3m
Real number (ℝ)

Distinct63
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.552
Minimum0
Maximum211
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:06.396142image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum211
Range211
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.539576675
Coefficient of variation (CV)3.569314868
Kurtosis404.4159115
Mean1.552
Median Absolute Deviation (MAD)0
Skewness16.30107829
Sum77600
Variance30.68690974
MonotonicityNot monotonic
2023-04-05T23:08:06.590509image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
5 986
 
2.0%
6 756
 
1.5%
7 505
 
1.0%
8 317
 
0.6%
9 225
 
0.4%
Other values (53) 1153
 
2.3%
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
ValueCountFrequency (%)
211 5
 
< 0.1%
149 4
 
< 0.1%
130 14
< 0.1%
114 4
 
< 0.1%
107 7
< 0.1%

ProfServ_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.23736
Minimum0
Maximum42
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:06.747553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.442366749
Coefficient of variation (CV)6.076705212
Kurtosis543.1740231
Mean0.23736
Median Absolute Deviation (MAD)0
Skewness20.80803992
Sum11868
Variance2.080421839
MonotonicityNot monotonic
2023-04-05T23:08:06.932883image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
5 91
 
0.2%
40 34
 
0.1%
9 27
 
0.1%
8 26
 
0.1%
6 26
 
0.1%
Other values (16) 90
 
0.2%
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
ValueCountFrequency (%)
42 9
 
< 0.1%
40 34
0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
27 2
 
< 0.1%

Education_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.38266
Minimum0
Maximum95
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:07.104477image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum95
Range95
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.128558653
Coefficient of variation (CV)5.562532413
Kurtosis739.0244771
Mean0.38266
Median Absolute Deviation (MAD)0
Skewness22.97968228
Sum19133
Variance4.53076194
MonotonicityNot monotonic
2023-04-05T23:08:07.244544image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
5 176
 
0.4%
6 110
 
0.2%
7 48
 
0.1%
9 34
 
0.1%
8 28
 
0.1%
Other values (28) 168
 
0.3%
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
ValueCountFrequency (%)
95 1
 
< 0.1%
83 12
< 0.1%
44 6
< 0.1%
43 5
< 0.1%
42 8
< 0.1%

GovtServices_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.33948
Minimum0
Maximum1127
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:07.349220image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum1127
Range1127
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.38762229
Coefficient of variation (CV)12.23431652
Kurtosis2880.094419
Mean1.33948
Median Absolute Deviation (MAD)0
Skewness47.9914472
Sum66974
Variance268.5541644
MonotonicityNot monotonic
2023-04-05T23:08:07.422902image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
5 547
 
1.1%
6 400
 
0.8%
7 319
 
0.6%
8 173
 
0.3%
9 139
 
0.3%
Other values (49) 808
 
1.6%
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
ValueCountFrequency (%)
1127 6
 
< 0.1%
390 33
0.1%
217 2
 
< 0.1%
171 1
 
< 0.1%
157 1
 
< 0.1%

Agri_amt_3m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:07.482704image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:07.670374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct235
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.2849898
Minimum0
Maximum440000
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:07.733631image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum440000
Range440000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6200.959492
Coefficient of variation (CV)28.14971414
Kurtosis2493.646558
Mean220.2849898
Median Absolute Deviation (MAD)0
Skewness45.61014742
Sum11014249.49
Variance38451898.63
MonotonicityNot monotonic
2023-04-05T23:08:07.803439image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49536
99.1%
199 18
 
< 0.1%
1000 9
 
< 0.1%
1299 9
 
< 0.1%
100000 8
 
< 0.1%
2800 8
 
< 0.1%
10000 7
 
< 0.1%
50000 7
 
< 0.1%
68355 6
 
< 0.1%
30000 6
 
< 0.1%
Other values (225) 386
 
0.8%
ValueCountFrequency (%)
0 49536
99.1%
10 1
 
< 0.1%
25 1
 
< 0.1%
50 6
 
< 0.1%
71.58 1
 
< 0.1%
ValueCountFrequency (%)
440000 1
< 0.1%
405200 1
< 0.1%
400000 1
< 0.1%
395000 1
< 0.1%
380000 1
< 0.1%

Airline_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1492
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4669.319054
Minimum0
Maximum2694664
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:07.878456image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3919.5
Maximum2694664
Range2694664
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55460.76836
Coefficient of variation (CV)11.87769945
Kurtosis1166.967589
Mean4669.319054
Median Absolute Deviation (MAD)0
Skewness30.18308024
Sum233465952.7
Variance3075896827
MonotonicityNot monotonic
2023-04-05T23:08:07.966038image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46359
92.7%
150 72
 
0.1%
300 66
 
0.1%
250 60
 
0.1%
200 52
 
0.1%
100 44
 
0.1%
450 40
 
0.1%
170811 33
 
0.1%
400 31
 
0.1%
350 28
 
0.1%
Other values (1482) 3215
 
6.4%
ValueCountFrequency (%)
0 46359
92.7%
50 2
 
< 0.1%
99 3
 
< 0.1%
100 44
 
0.1%
104.25 2
 
< 0.1%
ValueCountFrequency (%)
2694664 2
 
< 0.1%
2444185.67 8
< 0.1%
2417315 1
 
< 0.1%
2088682 2
 
< 0.1%
1972827 2
 
< 0.1%

transport_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6259
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6478.121951
Minimum0
Maximum2169027.5
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.050553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24000
Maximum2169027.5
Range2169027.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47412.96853
Coefficient of variation (CV)7.318937323
Kurtosis561.0998448
Mean6478.121951
Median Absolute Deviation (MAD)0
Skewness20.68576257
Sum323906097.6
Variance2247989585
MonotonicityNot monotonic
2023-04-05T23:08:08.128610image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
2 221
 
0.4%
1000 117
 
0.2%
500 77
 
0.2%
1 65
 
0.1%
2000 53
 
0.1%
200 45
 
0.1%
1500 43
 
0.1%
300 34
 
0.1%
4 33
 
0.1%
Other values (6249) 11742
 
23.5%
ValueCountFrequency (%)
0 37570
75.1%
1 65
 
0.1%
1.3 1
 
< 0.1%
2 221
 
0.4%
2.8 1
 
< 0.1%
ValueCountFrequency (%)
2169027.5 1
 
< 0.1%
1403342.66 25
0.1%
1150000 6
 
< 0.1%
1027529.2 1
 
< 0.1%
1019060 1
 
< 0.1%

Insurance_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6348
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9789.220463
Minimum0
Maximum4484200
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.221664image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42734.95
Maximum4484200
Range4484200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation70123.11161
Coefficient of variation (CV)7.163298843
Kurtosis1813.36226
Mean9789.220463
Median Absolute Deviation (MAD)0
Skewness34.35284618
Sum489461023.2
Variance4917250782
MonotonicityNot monotonic
2023-04-05T23:08:08.298124image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39445
78.9%
1116060 33
 
0.1%
530 33
 
0.1%
10000 27
 
0.1%
15000 26
 
0.1%
5000 26
 
0.1%
3801 21
 
< 0.1%
102250 20
 
< 0.1%
887 20
 
< 0.1%
52250 18
 
< 0.1%
Other values (6338) 10331
 
20.7%
ValueCountFrequency (%)
0 39445
78.9%
1 1
 
< 0.1%
2 5
 
< 0.1%
11 1
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
4484200 1
 
< 0.1%
4275963 5
< 0.1%
2176772.64 2
 
< 0.1%
1486353.22 1
 
< 0.1%
1329325.26 4
< 0.1%

Hotels_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6237
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6508.666604
Minimum0
Maximum4479268.69
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.382844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3356
95-th percentile25603.06
Maximum4479268.69
Range4479268.69
Interquartile range (IQR)356

Descriptive statistics

Standard deviation49810.4365
Coefficient of variation (CV)7.65294023
Kurtosis3040.056778
Mean6508.666604
Median Absolute Deviation (MAD)0
Skewness42.77689715
Sum325433330.2
Variance2481079584
MonotonicityNot monotonic
2023-04-05T23:08:08.463298image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36891
73.8%
3000 48
 
0.1%
2000 43
 
0.1%
1760 34
 
0.1%
1500 30
 
0.1%
5000 29
 
0.1%
10000 29
 
0.1%
1000 26
 
0.1%
4000 26
 
0.1%
2500 25
 
0.1%
Other values (6227) 12819
 
25.6%
ValueCountFrequency (%)
0 36891
73.8%
1 4
 
< 0.1%
2 18
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
4479268.69 2
 
< 0.1%
2260639.29 2
 
< 0.1%
1723207.74 7
< 0.1%
1576184.34 2
 
< 0.1%
1027180.5 4
< 0.1%

Railways_amt_3m
Real number (ℝ)

Distinct6459
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5483.707647
Minimum0
Maximum1080511
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.556461image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile22424.38
Maximum1080511
Range1080511
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32094.90815
Coefficient of variation (CV)5.852775206
Kurtosis295.10659
Mean5483.707647
Median Absolute Deviation (MAD)0
Skewness14.74147247
Sum274185382.4
Variance1030083129
MonotonicityNot monotonic
2023-04-05T23:08:08.634047image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39278
78.6%
500 45
 
0.1%
3897 33
 
0.1%
200 30
 
0.1%
300 29
 
0.1%
102.12 27
 
0.1%
57457.7 25
 
0.1%
100 24
 
< 0.1%
644062.26 20
 
< 0.1%
1 18
 
< 0.1%
Other values (6449) 10471
 
20.9%
ValueCountFrequency (%)
0 39278
78.6%
1 18
 
< 0.1%
1.21 1
 
< 0.1%
1.53 1
 
< 0.1%
2 4
 
< 0.1%
ValueCountFrequency (%)
1080511 2
 
< 0.1%
820633.41 11
< 0.1%
785491 2
 
< 0.1%
783356.6 1
 
< 0.1%
650000 2
 
< 0.1%

Airports_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.370073
Minimum0
Maximum14471.55
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.701812image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum14471.55
Range14471.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation190.1376108
Coefficient of variation (CV)43.50902394
Kurtosis2906.5728
Mean4.370073
Median Absolute Deviation (MAD)0
Skewness52.14727746
Sum218503.65
Variance36152.31103
MonotonicityNot monotonic
2023-04-05T23:08:08.764277image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 49945
99.9%
10300 12
 
< 0.1%
750 5
 
< 0.1%
150 3
 
< 0.1%
600 3
 
< 0.1%
1500 3
 
< 0.1%
5200 3
 
< 0.1%
500 2
 
< 0.1%
2175.53 2
 
< 0.1%
1920 2
 
< 0.1%
Other values (17) 20
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
121.09 1
 
< 0.1%
130 1
 
< 0.1%
150 3
 
< 0.1%
240 1
 
< 0.1%
ValueCountFrequency (%)
14471.55 1
 
< 0.1%
10300 12
< 0.1%
8732.42 1
 
< 0.1%
6195 1
 
< 0.1%
5200 3
 
< 0.1%

Utility_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14777
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20979.84211
Minimum0
Maximum4087763.19
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:08.921991image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median984.6
Q37823.165
95-th percentile67000
Maximum4087763.19
Range4087763.19
Interquartile range (IQR)7823.165

Descriptive statistics

Standard deviation141481.9163
Coefficient of variation (CV)6.743707393
Kurtosis547.0708129
Mean20979.84211
Median Absolute Deviation (MAD)984.6
Skewness21.14555362
Sum1048992105
Variance2.001713264 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:08.996280image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
2 204
 
0.4%
1947 149
 
0.3%
1178.82 139
 
0.3%
666 132
 
0.3%
2999 110
 
0.2%
597 94
 
0.2%
4000 84
 
0.2%
719 80
 
0.2%
1298 67
 
0.1%
Other values (14767) 28253
56.5%
ValueCountFrequency (%)
0 20688
41.4%
1 10
 
< 0.1%
1.18 1
 
< 0.1%
1.5 1
 
< 0.1%
2 204
 
0.4%
ValueCountFrequency (%)
4087763.19 34
0.1%
3293669.12 3
 
< 0.1%
2983747.64 14
< 0.1%
2179970.74 2
 
< 0.1%
2135000 2
 
< 0.1%

Retail_amt_3m
Real number (ℝ)

Distinct11163
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10277.3661
Minimum0
Maximum2444657.25
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.073430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34815.2775
95-th percentile40845.3
Maximum2444657.25
Range2444657.25
Interquartile range (IQR)4815.2775

Descriptive statistics

Standard deviation49404.26127
Coefficient of variation (CV)4.807093645
Kurtosis477.3922902
Mean10277.3661
Median Absolute Deviation (MAD)0
Skewness17.10848078
Sum513868305.1
Variance2440781032
MonotonicityNot monotonic
2023-04-05T23:08:09.148675image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
4000 155
 
0.3%
5000 88
 
0.2%
1000 88
 
0.2%
500 83
 
0.2%
2000 75
 
0.1%
10000 71
 
0.1%
300 56
 
0.1%
3000 55
 
0.1%
2500 48
 
0.1%
Other values (11153) 23556
47.1%
ValueCountFrequency (%)
0 25725
51.4%
1 10
 
< 0.1%
2 47
 
0.1%
3 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
2444657.25 1
 
< 0.1%
2028399.4 1
 
< 0.1%
1950777.21 1
 
< 0.1%
1700000 1
 
< 0.1%
1447823 11
< 0.1%

Medical_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct8057
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5956.067773
Minimum0
Maximum2402098
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.221626image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31402
95-th percentile23824.6725
Maximum2402098
Range2402098
Interquartile range (IQR)1402

Descriptive statistics

Standard deviation37995.19547
Coefficient of variation (CV)6.379241626
Kurtosis1358.903652
Mean5956.067773
Median Absolute Deviation (MAD)0
Skewness28.47865804
Sum297803388.7
Variance1443634878
MonotonicityNot monotonic
2023-04-05T23:08:09.297226image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1000 88
 
0.2%
800 78
 
0.2%
600 76
 
0.2%
500 73
 
0.1%
400 66
 
0.1%
10000 62
 
0.1%
1500 60
 
0.1%
386 58
 
0.1%
Other values (8047) 16998
34.0%
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1.74 1
 
< 0.1%
2 16
 
< 0.1%
2.09 1
 
< 0.1%
ValueCountFrequency (%)
2402098 3
< 0.1%
1920000 2
< 0.1%
1200021 1
 
< 0.1%
1004101.15 2
< 0.1%
991851 3
< 0.1%

Fuel_amt_3m
Real number (ℝ)

Distinct15280
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7818.260737
Minimum0
Maximum720806.32
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.372678image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median957.51
Q38259.5975
95-th percentile34593.08
Maximum720806.32
Range720806.32
Interquartile range (IQR)8259.5975

Descriptive statistics

Standard deviation19450.44167
Coefficient of variation (CV)2.487822078
Kurtosis207.5981641
Mean7818.260737
Median Absolute Deviation (MAD)957.51
Skewness9.776964854
Sum390913036.8
Variance378319681.1
MonotonicityNot monotonic
2023-04-05T23:08:09.442296image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
2023.6 248
 
0.5%
3035.4 237
 
0.5%
2020 208
 
0.4%
1011.8 201
 
0.4%
1010 182
 
0.4%
505 153
 
0.3%
4047.2 128
 
0.3%
2529.5 100
 
0.2%
505.9 97
 
0.2%
Other values (15270) 26479
53.0%
ValueCountFrequency (%)
0 21967
43.9%
40.47 1
 
< 0.1%
41.36 2
 
< 0.1%
50.5 1
 
< 0.1%
70.7 1
 
< 0.1%
ValueCountFrequency (%)
720806.32 3
< 0.1%
642096.54 2
< 0.1%
457796.21 2
< 0.1%
301441.79 3
< 0.1%
280881.76 3
< 0.1%

DeptStores_amt_3m
Real number (ℝ)

Distinct16736
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11766.24459
Minimum0
Maximum2500871.5
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.516475image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1025.85
Q36647.36
95-th percentile30875.1925
Maximum2500871.5
Range2500871.5
Interquartile range (IQR)6647.36

Descriptive statistics

Standard deviation64171.46191
Coefficient of variation (CV)5.453860949
Kurtosis434.6925681
Mean11766.24459
Median Absolute Deviation (MAD)1025.85
Skewness17.05207472
Sum588312229.7
Variance4117976523
MonotonicityNot monotonic
2023-04-05T23:08:09.593304image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1000 50
 
0.1%
10000 43
 
0.1%
3889.84 34
 
0.1%
900 33
 
0.1%
17463.93 33
 
0.1%
200 31
 
0.1%
25000 29
 
0.1%
3000 27
 
0.1%
5000 27
 
0.1%
Other values (16726) 29334
58.7%
ValueCountFrequency (%)
0 20359
40.7%
1 6
 
< 0.1%
1.36 1
 
< 0.1%
2 1
 
< 0.1%
2.34 2
 
< 0.1%
ValueCountFrequency (%)
2500871.5 3
 
< 0.1%
2428372 1
 
< 0.1%
2059552.18 8
< 0.1%
1392592.48 4
< 0.1%
1307000 2
 
< 0.1%

Food_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5214
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1385.462862
Minimum0
Maximum1096500
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.668509image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3485
95-th percentile5079.79
Maximum1096500
Range1096500
Interquartile range (IQR)485

Descriptive statistics

Standard deviation14397.16652
Coefficient of variation (CV)10.39159325
Kurtosis3266.876924
Mean1385.462862
Median Absolute Deviation (MAD)0
Skewness49.93555124
Sum69273143.11
Variance207278403.8
MonotonicityNot monotonic
2023-04-05T23:08:09.741764image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34180
68.4%
2 92
 
0.2%
500 73
 
0.1%
400 57
 
0.1%
1000 50
 
0.1%
450 49
 
0.1%
200 47
 
0.1%
300 46
 
0.1%
480 46
 
0.1%
4 43
 
0.1%
Other values (5204) 15317
30.6%
ValueCountFrequency (%)
0 34180
68.4%
1 3
 
< 0.1%
2 92
 
0.2%
3.12 1
 
< 0.1%
4 43
 
0.1%
ValueCountFrequency (%)
1096500 2
 
< 0.1%
1046805 3
< 0.1%
539123 1
 
< 0.1%
521890 1
 
< 0.1%
488020 5
< 0.1%

Auto_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1867
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2167.957446
Minimum0
Maximum1219987
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:09.815234image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4747.1
Maximum1219987
Range1219987
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26685.79818
Coefficient of variation (CV)12.30918911
Kurtosis777.9184609
Mean2167.957446
Median Absolute Deviation (MAD)0
Skewness25.52549873
Sum108397872.3
Variance712131824.5
MonotonicityNot monotonic
2023-04-05T23:08:09.973782image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46021
92.0%
10000 56
 
0.1%
670267.04 33
 
0.1%
25000 29
 
0.1%
11000 27
 
0.1%
3000 25
 
0.1%
5000 24
 
< 0.1%
1000 23
 
< 0.1%
2000 21
 
< 0.1%
21000 21
 
< 0.1%
Other values (1857) 3720
 
7.4%
ValueCountFrequency (%)
0 46021
92.0%
59 2
 
< 0.1%
60 2
 
< 0.1%
66 1
 
< 0.1%
84 1
 
< 0.1%
ValueCountFrequency (%)
1219987 4
 
< 0.1%
802400 1
 
< 0.1%
800000 4
 
< 0.1%
709100 4
 
< 0.1%
670267.04 33
0.1%

ClothStores_amt_3m
Real number (ℝ)

Distinct12156
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9433.808793
Minimum0
Maximum1154700
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.051092image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median499
Q37897.24
95-th percentile39944.9
Maximum1154700
Range1154700
Interquartile range (IQR)7897.24

Descriptive statistics

Standard deviation31098.84787
Coefficient of variation (CV)3.296531502
Kurtosis291.5345429
Mean9433.808793
Median Absolute Deviation (MAD)499
Skewness13.04381894
Sum471690439.6
Variance967138338.6
MonotonicityNot monotonic
2023-04-05T23:08:10.125683image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24277
48.6%
5000 54
 
0.1%
3000 52
 
0.1%
1000 49
 
0.1%
400 48
 
0.1%
2000 43
 
0.1%
1500 42
 
0.1%
1499 36
 
0.1%
599 34
 
0.1%
999 34
 
0.1%
Other values (12146) 25331
50.7%
ValueCountFrequency (%)
0 24277
48.6%
2 27
 
0.1%
3.1 1
 
< 0.1%
10 7
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1154700 3
< 0.1%
964208.44 3
< 0.1%
837031.06 4
< 0.1%
800000 1
 
< 0.1%
789448.5 1
 
< 0.1%

MiscServices_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5445
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2870.836041
Minimum0
Maximum1568000
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.200828image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3308
95-th percentile11139.15
Maximum1568000
Range1568000
Interquartile range (IQR)308

Descriptive statistics

Standard deviation21446.42166
Coefficient of variation (CV)7.470444621
Kurtosis1377.045698
Mean2870.836041
Median Absolute Deviation (MAD)0
Skewness30.16463497
Sum143541802.1
Variance459949002.1
MonotonicityNot monotonic
2023-04-05T23:08:10.275448image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
2 1374
 
2.7%
1000 73
 
0.1%
500 68
 
0.1%
600 64
 
0.1%
2000 60
 
0.1%
5000 56
 
0.1%
2500 53
 
0.1%
3000 52
 
0.1%
6000 51
 
0.1%
Other values (5435) 13364
 
26.7%
ValueCountFrequency (%)
0 34785
69.6%
1 10
 
< 0.1%
2 1374
 
2.7%
3 1
 
< 0.1%
4 11
 
< 0.1%
ValueCountFrequency (%)
1568000 1
< 0.1%
1105500 2
< 0.1%
1000705.7 2
< 0.1%
833000 2
< 0.1%
810929 2
< 0.1%

HomeF_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1244
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1107.691418
Minimum0
Maximum521180.38
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.355081image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile800
Maximum521180.38
Range521180.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11198.17701
Coefficient of variation (CV)10.10947348
Kurtosis961.430417
Mean1107.691418
Median Absolute Deviation (MAD)0
Skewness26.28062187
Sum55384570.89
Variance125399168.3
MonotonicityNot monotonic
2023-04-05T23:08:10.431245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47285
94.6%
5000 32
 
0.1%
20000 25
 
0.1%
10000 21
 
< 0.1%
1000 16
 
< 0.1%
15000 13
 
< 0.1%
4200 13
 
< 0.1%
4449 12
 
< 0.1%
8000 12
 
< 0.1%
30000 12
 
< 0.1%
Other values (1234) 2559
 
5.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
90 1
 
< 0.1%
ValueCountFrequency (%)
521180.38 2
 
< 0.1%
516155 1
 
< 0.1%
500000 6
< 0.1%
387326 1
 
< 0.1%
353000 1
 
< 0.1%

Electronics_amt_3m
Real number (ℝ)

Distinct8450
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7785.50485
Minimum0
Maximum1075000
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.507268image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32105
95-th percentile36104.53
Maximum1075000
Range1075000
Interquartile range (IQR)2105

Descriptive statistics

Standard deviation37669.26346
Coefficient of variation (CV)4.838384175
Kurtosis260.1614027
Mean7785.50485
Median Absolute Deviation (MAD)0
Skewness13.72312102
Sum389275242.5
Variance1418973409
MonotonicityNot monotonic
2023-04-05T23:08:10.583607image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
199 103
 
0.2%
1499 57
 
0.1%
549 52
 
0.1%
299 50
 
0.1%
2 42
 
0.1%
10000 41
 
0.1%
2000 41
 
0.1%
2999 40
 
0.1%
15000 36
 
0.1%
Other values (8440) 17426
34.9%
ValueCountFrequency (%)
0 32112
64.2%
1 25
 
0.1%
2 42
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
1075000 1
 
< 0.1%
1004027.56 3
 
< 0.1%
959690 3
 
< 0.1%
942423 13
< 0.1%
790833.6 3
 
< 0.1%

MusicStores_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct246
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.767819
Minimum0
Maximum272142
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.656029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum272142
Range272142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2954.615352
Coefficient of variation (CV)33.66399422
Kurtosis7219.326039
Mean87.767819
Median Absolute Deviation (MAD)0
Skewness80.00078775
Sum4388390.95
Variance8729751.876
MonotonicityNot monotonic
2023-04-05T23:08:10.731143image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49307
98.6%
99 22
 
< 0.1%
2000 18
 
< 0.1%
149 14
 
< 0.1%
5000 14
 
< 0.1%
75 13
 
< 0.1%
1499 13
 
< 0.1%
449 13
 
< 0.1%
269 12
 
< 0.1%
169 11
 
< 0.1%
Other values (236) 563
 
1.1%
ValueCountFrequency (%)
0 49307
98.6%
5 3
 
< 0.1%
7 1
 
< 0.1%
15 5
 
< 0.1%
18 4
 
< 0.1%
ValueCountFrequency (%)
272142 5
< 0.1%
88411 1
 
< 0.1%
50179 2
 
< 0.1%
49500 2
 
< 0.1%
39000 1
 
< 0.1%

Restaurants_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14564
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5916.247728
Minimum0
Maximum1020000
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:10.809096image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median680.1
Q34861
95-th percentile24971
Maximum1020000
Range1020000
Interquartile range (IQR)4861

Descriptive statistics

Standard deviation22675.5409
Coefficient of variation (CV)3.832757169
Kurtosis668.8097281
Mean5916.247728
Median Absolute Deviation (MAD)680.1
Skewness20.79086653
Sum295812386.4
Variance514180154.9
MonotonicityNot monotonic
2023-04-05T23:08:10.882200image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
2 399
 
0.8%
4 152
 
0.3%
300 42
 
0.1%
6 37
 
0.1%
2061.65 33
 
0.1%
220 32
 
0.1%
1000 32
 
0.1%
900 31
 
0.1%
400 30
 
0.1%
Other values (14554) 28958
57.9%
ValueCountFrequency (%)
0 20254
40.5%
1 4
 
< 0.1%
2 399
 
0.8%
4 152
 
0.3%
6 37
 
0.1%
ValueCountFrequency (%)
1020000 1
 
< 0.1%
1000000 1
 
< 0.1%
863465.05 9
< 0.1%
657847.38 7
< 0.1%
495000 1
 
< 0.1%

DigitalGoods_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1822
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2473.969376
Minimum0
Maximum948600
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.034443image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1891
Maximum948600
Range948600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30509.16017
Coefficient of variation (CV)12.33206865
Kurtosis531.4836965
Mean2473.969376
Median Absolute Deviation (MAD)0
Skewness21.24664222
Sum123698468.8
Variance930808854.4
MonotonicityNot monotonic
2023-04-05T23:08:11.103029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
2 169
 
0.3%
1300 120
 
0.2%
390 112
 
0.2%
299 106
 
0.2%
200 84
 
0.2%
387 71
 
0.1%
20 64
 
0.1%
567 64
 
0.1%
258 55
 
0.1%
Other values (1812) 5112
 
10.2%
ValueCountFrequency (%)
0 44043
88.1%
1 42
 
0.1%
2 169
 
0.3%
4 14
 
< 0.1%
5 3
 
< 0.1%
ValueCountFrequency (%)
948600 8
 
< 0.1%
884000 2
 
< 0.1%
865000 20
< 0.1%
811681.72 2
 
< 0.1%
602499 5
 
< 0.1%

Alcohol_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2019
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean797.6000446
Minimum0
Maximum399994
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.179472image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3683
Maximum399994
Range399994
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6130.755373
Coefficient of variation (CV)7.686503297
Kurtosis1671.293833
Mean797.6000446
Median Absolute Deviation (MAD)0
Skewness32.97707862
Sum39880002.23
Variance37586161.44
MonotonicityNot monotonic
2023-04-05T23:08:11.255562image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43436
86.9%
900 48
 
0.1%
600 47
 
0.1%
360 42
 
0.1%
1200 34
 
0.1%
400 34
 
0.1%
800 31
 
0.1%
720 30
 
0.1%
300 30
 
0.1%
540 30
 
0.1%
Other values (2009) 6238
 
12.5%
ValueCountFrequency (%)
0 43436
86.9%
60 1
 
< 0.1%
90 4
 
< 0.1%
104 1
 
< 0.1%
105 2
 
< 0.1%
ValueCountFrequency (%)
399994 2
< 0.1%
390730 1
 
< 0.1%
390635 1
 
< 0.1%
231400 2
< 0.1%
200240 3
< 0.1%

Books_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1938
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634.0098318
Minimum0
Maximum949000
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.337631image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1526
Maximum949000
Range949000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10100.5045
Coefficient of variation (CV)15.93114805
Kurtosis3809.320487
Mean634.0098318
Median Absolute Deviation (MAD)0
Skewness52.38559939
Sum31700491.59
Variance102020191.1
MonotonicityNot monotonic
2023-04-05T23:08:11.411056image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45427
90.9%
450 25
 
0.1%
400 22
 
< 0.1%
300 22
 
< 0.1%
40000 20
 
< 0.1%
900 19
 
< 0.1%
1000 18
 
< 0.1%
2500 18
 
< 0.1%
600 17
 
< 0.1%
1700 17
 
< 0.1%
Other values (1928) 4395
 
8.8%
ValueCountFrequency (%)
0 45427
90.9%
1 3
 
< 0.1%
1.51 1
 
< 0.1%
8 2
 
< 0.1%
10 5
 
< 0.1%
ValueCountFrequency (%)
949000 2
 
< 0.1%
464107.59 4
< 0.1%
400000 1
 
< 0.1%
368130 6
< 0.1%
281550 1
 
< 0.1%

Jewelry_amt_3m
Real number (ℝ)

Distinct2303
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5020.164728
Minimum0
Maximum1312235
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.481942image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20387.2
Maximum1312235
Range1312235
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31291.24714
Coefficient of variation (CV)6.233111628
Kurtosis274.1977494
Mean5020.164728
Median Absolute Deviation (MAD)0
Skewness13.52489059
Sum251008236.4
Variance979142147.6
MonotonicityNot monotonic
2023-04-05T23:08:11.562619image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44421
88.8%
10000 105
 
0.2%
5000 78
 
0.2%
20000 76
 
0.2%
30000 53
 
0.1%
6000 51
 
0.1%
2000 51
 
0.1%
4000 45
 
0.1%
15000 41
 
0.1%
50000 38
 
0.1%
Other values (2293) 5041
 
10.1%
ValueCountFrequency (%)
0 44421
88.8%
10 2
 
< 0.1%
110 1
 
< 0.1%
119 3
 
< 0.1%
120 1
 
< 0.1%
ValueCountFrequency (%)
1312235 1
< 0.1%
1126230 1
< 0.1%
832650 2
< 0.1%
829200 2
< 0.1%
724000 1
< 0.1%

DirectM_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct836
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440.4139112
Minimum0
Maximum1839140.65
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.641608image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile149
Maximum1839140.65
Range1839140.65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16126.08507
Coefficient of variation (CV)36.61574865
Kurtosis10640.73601
Mean440.4139112
Median Absolute Deviation (MAD)0
Skewness97.61371505
Sum22020695.56
Variance260050619.8
MonotonicityNot monotonic
2023-04-05T23:08:11.713685image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47389
94.8%
199 390
 
0.8%
649 338
 
0.7%
499 169
 
0.3%
149 115
 
0.2%
398 29
 
0.1%
2 26
 
0.1%
1298 19
 
< 0.1%
998 15
 
< 0.1%
501 11
 
< 0.1%
Other values (826) 1499
 
3.0%
ValueCountFrequency (%)
0 47389
94.8%
1 1
 
< 0.1%
2 26
 
0.1%
12 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
1839140.65 3
< 0.1%
1115580.42 1
 
< 0.1%
516502.12 1
 
< 0.1%
351866.94 1
 
< 0.1%
330896.88 1
 
< 0.1%

Cash_amt_3m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.776359image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:11.820883image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.913654
Minimum0
Maximum149644.47
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.875205image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum149644.47
Range149644.47
Interquartile range (IQR)0

Descriptive statistics

Standard deviation967.3857349
Coefficient of variation (CV)108.5285266
Kurtosis22921.57892
Mean8.913654
Median Absolute Deviation (MAD)0
Skewness148.9790539
Sum445682.7
Variance935835.1601
MonotonicityNot monotonic
2023-04-05T23:08:11.927823image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
3393.16 4
 
< 0.1%
4457.23 4
 
< 0.1%
5007.12 3
 
< 0.1%
319.01 2
 
< 0.1%
149644.47 2
 
< 0.1%
21072.71 2
 
< 0.1%
2399.01 1
 
< 0.1%
8469.32 1
 
< 0.1%
Other values (7) 7
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
319.01 2
 
< 0.1%
754.41 1
 
< 0.1%
2009.57 1
 
< 0.1%
ValueCountFrequency (%)
149644.47 2
< 0.1%
27988.24 1
< 0.1%
21072.71 2
< 0.1%
8469.32 1
< 0.1%
5013.32 1
< 0.1%

FS_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.366
Minimum0
Maximum30000
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:11.983722image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30000
Range30000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation174.5065703
Coefficient of variation (CV)127.7500515
Kurtosis25755.09187
Mean1.366
Median Absolute Deviation (MAD)0
Skewness159.7054686
Sum68300
Variance30452.54309
MonotonicityNot monotonic
2023-04-05T23:08:12.028184image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
30000 1
 
< 0.1%
24900 1
 
< 0.1%
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
24900 1
 
< 0.1%
30000 1
 
< 0.1%
ValueCountFrequency (%)
30000 1
 
< 0.1%
24900 1
 
< 0.1%
200 67
 
0.1%
0 49931
99.9%

RentPayments_amt_3m
Real number (ℝ)

Distinct6705
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17250.93866
Minimum0
Maximum1013828
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.097353image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile106470.675
Maximum1013828
Range1013828
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51878.21575
Coefficient of variation (CV)3.007269156
Kurtosis42.62888392
Mean17250.93866
Median Absolute Deviation (MAD)0
Skewness5.359033025
Sum862546933
Variance2691349269
MonotonicityNot monotonic
2023-04-05T23:08:12.172061image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38583
77.2%
20300 65
 
0.1%
10150 58
 
0.1%
3540 57
 
0.1%
25375 42
 
0.1%
20200 40
 
0.1%
40600 30
 
0.1%
30420 28
 
0.1%
20310 27
 
0.1%
30300 25
 
0.1%
Other values (6695) 11045
 
22.1%
ValueCountFrequency (%)
0 38583
77.2%
1 1
 
< 0.1%
1.01 1
 
< 0.1%
2 18
 
< 0.1%
5.11 1
 
< 0.1%
ValueCountFrequency (%)
1013828 1
< 0.1%
959020 1
< 0.1%
891620.5 1
< 0.1%
807058 1
< 0.1%
797900 2
< 0.1%

WalletLoad_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4467
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3405.023854
Minimum0
Maximum1835364.3
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.246669image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20336.72
Maximum1835364.3
Range1835364.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20662.81433
Coefficient of variation (CV)6.06833174
Kurtosis2728.405834
Mean3405.023854
Median Absolute Deviation (MAD)0
Skewness38.26647813
Sum170251192.7
Variance426951896
MonotonicityNot monotonic
2023-04-05T23:08:12.321629image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1023 139
 
0.3%
1000 123
 
0.2%
500 105
 
0.2%
2000 103
 
0.2%
4000 103
 
0.2%
10230 99
 
0.2%
2046 85
 
0.2%
5115 81
 
0.2%
20460 79
 
0.2%
Other values (4457) 9634
 
19.3%
ValueCountFrequency (%)
0 39449
78.9%
1 5
 
< 0.1%
1.02 5
 
< 0.1%
1.03 1
 
< 0.1%
2 43
 
0.1%
ValueCountFrequency (%)
1835364.3 2
 
< 0.1%
684317.7 4
< 0.1%
656226.57 6
< 0.1%
337932 7
< 0.1%
323330 2
 
< 0.1%

BusinessServ_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct10073
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10236.93259
Minimum0
Maximum4905650
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.483740image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31399
95-th percentile20072
Maximum4905650
Range4905650
Interquartile range (IQR)1399

Descriptive statistics

Standard deviation110315.3813
Coefficient of variation (CV)10.77621449
Kurtosis1051.347246
Mean10236.93259
Median Absolute Deviation (MAD)0
Skewness28.70445734
Sum511846629.6
Variance1.216948335 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:12.561226image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1000 94
 
0.2%
600 65
 
0.1%
899 63
 
0.1%
1500 63
 
0.1%
1499 60
 
0.1%
500 56
 
0.1%
2 49
 
0.1%
400 48
 
0.1%
3000 45
 
0.1%
Other values (10063) 20484
41.0%
ValueCountFrequency (%)
0 28973
57.9%
1 17
 
< 0.1%
2 49
 
0.1%
3 1
 
< 0.1%
4 9
 
< 0.1%
ValueCountFrequency (%)
4905650 11
< 0.1%
3121264.01 1
 
< 0.1%
2828574 14
< 0.1%
2697100 4
 
< 0.1%
1894211.09 12
< 0.1%

ProfServ_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2179
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2725.70208
Minimum0
Maximum1500000
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.636218image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6807.2
Maximum1500000
Range1500000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27657.61293
Coefficient of variation (CV)10.14696842
Kurtosis1000.913767
Mean2725.70208
Median Absolute Deviation (MAD)0
Skewness26.89576097
Sum136285104
Variance764943553.1
MonotonicityNot monotonic
2023-04-05T23:08:12.711454image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44022
88.0%
500 95
 
0.2%
1000 76
 
0.2%
1500 68
 
0.1%
3000 66
 
0.1%
5000 65
 
0.1%
10000 61
 
0.1%
4032 52
 
0.1%
2000 50
 
0.1%
400 40
 
0.1%
Other values (2169) 5405
 
10.8%
ValueCountFrequency (%)
0 44022
88.0%
1 8
 
< 0.1%
10 3
 
< 0.1%
29 2
 
< 0.1%
31 1
 
< 0.1%
ValueCountFrequency (%)
1500000 2
< 0.1%
1302900 2
< 0.1%
1300000 1
< 0.1%
1150000 1
< 0.1%
1125000 1
< 0.1%

Education_amt_3m
Real number (ℝ)

Distinct3859
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6434.501254
Minimum0
Maximum1505584
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.795142image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile34443.63
Maximum1505584
Range1505584
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37406.22845
Coefficient of variation (CV)5.813384281
Kurtosis451.9611095
Mean6434.501254
Median Absolute Deviation (MAD)0
Skewness17.12044735
Sum321725062.7
Variance1399225926
MonotonicityNot monotonic
2023-04-05T23:08:12.868689image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41554
83.1%
2 572
 
1.1%
455 41
 
0.1%
1000 40
 
0.1%
10000 39
 
0.1%
500 37
 
0.1%
15000 35
 
0.1%
68215.44 33
 
0.1%
3000 31
 
0.1%
20000 30
 
0.1%
Other values (3849) 7588
 
15.2%
ValueCountFrequency (%)
0 41554
83.1%
1 1
 
< 0.1%
1.03 1
 
< 0.1%
2 572
 
1.1%
3 1
 
< 0.1%
ValueCountFrequency (%)
1505584 3
< 0.1%
1250000 5
< 0.1%
1186450.01 3
< 0.1%
928098.23 1
 
< 0.1%
898741 6
< 0.1%

GovtServices_amt_3m
Real number (ℝ)

SKEWED  ZEROS 

Distinct7060
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18016.19656
Minimum0
Maximum15000000
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:12.945567image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3300
95-th percentile25266.326
Maximum15000000
Range15000000
Interquartile range (IQR)300

Descriptive statistics

Standard deviation389880.2572
Coefficient of variation (CV)21.64054194
Kurtosis1436.625262
Mean18016.19656
Median Absolute Deviation (MAD)0
Skewness37.52586981
Sum900809827.8
Variance1.52006615 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:13.016519image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
50 113
 
0.2%
1526.55 92
 
0.2%
500 83
 
0.2%
201.76 70
 
0.1%
200 61
 
0.1%
100 53
 
0.1%
1000 45
 
0.1%
50445 43
 
0.1%
2000 41
 
0.1%
Other values (7050) 12826
 
25.7%
ValueCountFrequency (%)
0 36573
73.1%
3.03 2
 
< 0.1%
5.06 3
 
< 0.1%
7 1
 
< 0.1%
8.26 11
 
< 0.1%
ValueCountFrequency (%)
15000000 33
0.1%
2458136 5
 
< 0.1%
2281696.4 1
 
< 0.1%
1654514 1
 
< 0.1%
1594670.03 2
 
< 0.1%

Agri_6m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.077482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:13.124703image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01372
Minimum0
Maximum17
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.174368image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1941456037
Coefficient of variation (CV)14.15055421
Kurtosis2097.9857
Mean0.01372
Median Absolute Deviation (MAD)0
Skewness34.78914986
Sum686
Variance0.03769251545
MonotonicityNot monotonic
2023-04-05T23:08:13.227232image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
6 3
 
< 0.1%
5 3
 
< 0.1%
9 2
 
< 0.1%
7 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
14 1
 
< 0.1%
9 2
< 0.1%
7 1
 
< 0.1%
6 3
< 0.1%

Airline_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22376
Minimum0
Maximum86
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.291084image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.227013842
Coefficient of variation (CV)9.952689678
Kurtosis1033.304052
Mean0.22376
Median Absolute Deviation (MAD)0
Skewness29.50974303
Sum11188
Variance4.959590654
MonotonicityNot monotonic
2023-04-05T23:08:13.351453image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
5 107
 
0.2%
6 59
 
0.1%
7 49
 
0.1%
10 38
 
0.1%
8 34
 
0.1%
Other values (20) 146
 
0.3%
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
ValueCountFrequency (%)
86 12
< 0.1%
80 14
< 0.1%
47 8
< 0.1%
38 2
 
< 0.1%
37 1
 
< 0.1%

transport_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.10542
Minimum0
Maximum199
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.420538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum199
Range199
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.996150907
Coefficient of variation (CV)5.424319179
Kurtosis627.6198803
Mean1.10542
Median Absolute Deviation (MAD)0
Skewness21.19144641
Sum55271
Variance35.9538257
MonotonicityNot monotonic
2023-04-05T23:08:13.493630image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
5 448
 
0.9%
6 330
 
0.7%
7 249
 
0.5%
8 198
 
0.4%
9 136
 
0.3%
Other values (63) 1140
 
2.3%
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
ValueCountFrequency (%)
199 25
0.1%
148 1
 
< 0.1%
122 1
 
< 0.1%
120 2
 
< 0.1%
106 1
 
< 0.1%

Insurance_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57774
Minimum0
Maximum348
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.571833image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum348
Range348
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.488919636
Coefficient of variation (CV)7.769792011
Kurtosis3666.095835
Mean0.57774
Median Absolute Deviation (MAD)0
Skewness51.17353581
Sum28887
Variance20.1503995
MonotonicityNot monotonic
2023-04-05T23:08:13.723567image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
5 177
 
0.4%
6 119
 
0.2%
7 78
 
0.2%
12 42
 
0.1%
34 40
 
0.1%
Other values (36) 369
 
0.7%
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
ValueCountFrequency (%)
348 5
< 0.1%
94 9
< 0.1%
91 7
< 0.1%
89 3
 
< 0.1%
73 2
 
< 0.1%

Hotels_6m
Real number (ℝ)

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72448
Minimum0
Maximum65
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.793251image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum65
Range65
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.03482961
Coefficient of variation (CV)2.808676029
Kurtosis156.4901343
Mean0.72448
Median Absolute Deviation (MAD)0
Skewness8.30915014
Sum36224
Variance4.14053154
MonotonicityNot monotonic
2023-04-05T23:08:13.855432image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
5 569
 
1.1%
6 395
 
0.8%
7 281
 
0.6%
8 222
 
0.4%
10 119
 
0.2%
Other values (23) 452
 
0.9%
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
ValueCountFrequency (%)
65 6
< 0.1%
38 3
< 0.1%
36 1
 
< 0.1%
31 2
 
< 0.1%
29 3
< 0.1%

Railways_6m
Real number (ℝ)

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72686
Minimum0
Maximum88
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:13.931521image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum88
Range88
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.135737744
Coefficient of variation (CV)4.314087642
Kurtosis341.1364602
Mean0.72686
Median Absolute Deviation (MAD)0
Skewness15.25758491
Sum36343
Variance9.832851197
MonotonicityNot monotonic
2023-04-05T23:08:13.995404image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
5 388
 
0.8%
6 313
 
0.6%
7 208
 
0.4%
8 180
 
0.4%
10 155
 
0.3%
Other values (35) 627
 
1.3%
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
ValueCountFrequency (%)
88 20
< 0.1%
80 1
 
< 0.1%
67 10
< 0.1%
65 2
 
< 0.1%
61 4
 
< 0.1%

Airports_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00146
Minimum0
Maximum5
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.052898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04917231699
Coefficient of variation (CV)33.67966917
Kurtosis3033.124738
Mean0.00146
Median Absolute Deviation (MAD)0
Skewness46.50959616
Sum73
Variance0.002417916758
MonotonicityNot monotonic
2023-04-05T23:08:14.105421image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
2 14
 
< 0.1%
1 40
 
0.1%
0 49945
99.9%

Utility_6m
Real number (ℝ)

Distinct90
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5979
Minimum0
Maximum389
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.175816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile13
Maximum389
Range389
Interquartile range (IQR)4

Descriptive statistics

Standard deviation13.89091627
Coefficient of variation (CV)3.860840009
Kurtosis489.6128409
Mean3.5979
Median Absolute Deviation (MAD)1
Skewness19.79756961
Sum179895
Variance192.9575547
MonotonicityNot monotonic
2023-04-05T23:08:14.253026image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
5 2048
 
4.1%
6 1642
 
3.3%
7 1255
 
2.5%
8 891
 
1.8%
9 832
 
1.7%
Other values (80) 4042
 
8.1%
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
ValueCountFrequency (%)
389 34
0.1%
285 19
< 0.1%
274 1
 
< 0.1%
269 4
 
< 0.1%
176 14
< 0.1%

Retail_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct71
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.84948
Minimum0
Maximum1044
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.335438image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum1044
Range1044
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.256715263
Coefficient of variation (CV)5.005036693
Kurtosis4258.902872
Mean1.84948
Median Absolute Deviation (MAD)0
Skewness52.81860742
Sum92474
Variance85.68677747
MonotonicityNot monotonic
2023-04-05T23:08:14.412606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
5 1258
 
2.5%
6 838
 
1.7%
7 675
 
1.4%
8 441
 
0.9%
9 401
 
0.8%
Other values (61) 1420
 
2.8%
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
ValueCountFrequency (%)
1044 1
 
< 0.1%
470 2
 
< 0.1%
465 3
< 0.1%
378 2
 
< 0.1%
369 5
< 0.1%

Medical_6m
Real number (ℝ)

Distinct52
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.43778
Minimum0
Maximum83
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.486798image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum83
Range83
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.608189165
Coefficient of variation (CV)2.509555819
Kurtosis71.74185192
Mean1.43778
Median Absolute Deviation (MAD)0
Skewness6.334131441
Sum71889
Variance13.01902905
MonotonicityNot monotonic
2023-04-05T23:08:14.555276image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
5 1018
 
2.0%
6 752
 
1.5%
7 616
 
1.2%
8 470
 
0.9%
9 318
 
0.6%
Other values (42) 1617
 
3.2%
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
ValueCountFrequency (%)
83 4
< 0.1%
65 3
 
< 0.1%
61 8
< 0.1%
58 4
< 0.1%
54 5
< 0.1%

Fuel_6m
Real number (ℝ)

Distinct77
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.47412
Minimum0
Maximum193
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.626497image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile14
Maximum193
Range193
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.213805795
Coefficient of variation (CV)1.788598492
Kurtosis65.06113242
Mean3.47412
Median Absolute Deviation (MAD)1
Skewness5.34325986
Sum173706
Variance38.61138245
MonotonicityNot monotonic
2023-04-05T23:08:14.702155image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
5 2121
 
4.2%
6 1802
 
3.6%
7 1399
 
2.8%
8 1208
 
2.4%
9 1095
 
2.2%
Other values (67) 5362
 
10.7%
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
ValueCountFrequency (%)
193 1
 
< 0.1%
138 3
< 0.1%
112 1
 
< 0.1%
110 4
< 0.1%
96 1
 
< 0.1%

DeptStores_6m
Real number (ℝ)

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.76012
Minimum0
Maximum187
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:14.867722image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile16
Maximum187
Range187
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.832164735
Coefficient of variation (CV)2.082956059
Kurtosis65.82871473
Mean3.76012
Median Absolute Deviation (MAD)1
Skewness6.028340139
Sum188006
Variance61.34280444
MonotonicityNot monotonic
2023-04-05T23:08:14.937469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
5 1889
 
3.8%
6 1340
 
2.7%
7 1108
 
2.2%
8 943
 
1.9%
9 814
 
1.6%
Other values (82) 5430
 
10.9%
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
ValueCountFrequency (%)
187 3
< 0.1%
140 5
< 0.1%
139 1
 
< 0.1%
133 1
 
< 0.1%
124 2
 
< 0.1%

Food_6m
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91748
Minimum0
Maximum114
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.010656image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum114
Range114
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.608962741
Coefficient of variation (CV)2.843618107
Kurtosis433.8072451
Mean0.91748
Median Absolute Deviation (MAD)0
Skewness13.85156464
Sum45874
Variance6.806686583
MonotonicityNot monotonic
2023-04-05T23:08:15.078682image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
5 723
 
1.4%
6 470
 
0.9%
7 316
 
0.6%
8 220
 
0.4%
9 194
 
0.4%
Other values (32) 618
 
1.2%
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
ValueCountFrequency (%)
114 5
< 0.1%
80 1
 
< 0.1%
68 1
 
< 0.1%
56 2
 
< 0.1%
55 2
 
< 0.1%

Auto_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15662
Minimum0
Maximum57
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.140888image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum57
Range57
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.435385447
Coefficient of variation (CV)9.1647647
Kurtosis970.2156726
Mean0.15662
Median Absolute Deviation (MAD)0
Skewness28.46302955
Sum7831
Variance2.060331382
MonotonicityNot monotonic
2023-04-05T23:08:15.192166image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
5 36
 
0.1%
33 33
 
0.1%
6 25
 
0.1%
57 16
 
< 0.1%
12 12
 
< 0.1%
Other values (9) 42
 
0.1%
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
ValueCountFrequency (%)
57 16
< 0.1%
33 33
0.1%
17 4
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%

ClothStores_6m
Real number (ℝ)

Distinct41
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.89714
Minimum0
Maximum59
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.257418image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile8
Maximum59
Range59
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.372338547
Coefficient of variation (CV)1.777590766
Kurtosis34.01497166
Mean1.89714
Median Absolute Deviation (MAD)1
Skewness4.244303483
Sum94857
Variance11.37266727
MonotonicityNot monotonic
2023-04-05T23:08:15.322957image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
5 1730
 
3.5%
6 1223
 
2.4%
7 878
 
1.8%
8 622
 
1.2%
9 504
 
1.0%
Other values (31) 1742
 
3.5%
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
ValueCountFrequency (%)
59 1
 
< 0.1%
57 9
< 0.1%
45 11
< 0.1%
42 1
 
< 0.1%
38 2
 
< 0.1%

MiscServices_6m
Real number (ℝ)

Distinct58
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90552
Minimum0
Maximum93
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.397569image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.282427306
Coefficient of variation (CV)3.624908677
Kurtosis177.2661933
Mean0.90552
Median Absolute Deviation (MAD)0
Skewness11.07163845
Sum45276
Variance10.77432902
MonotonicityNot monotonic
2023-04-05T23:08:15.468508image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
5 456
 
0.9%
6 334
 
0.7%
7 222
 
0.4%
8 139
 
0.3%
9 101
 
0.2%
Other values (48) 721
 
1.4%
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
ValueCountFrequency (%)
93 3
 
< 0.1%
78 1
 
< 0.1%
77 3
 
< 0.1%
66 10
< 0.1%
65 6
< 0.1%

HomeF_6m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07982
Minimum0
Maximum23
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.528996image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4301307567
Coefficient of variation (CV)5.388759167
Kurtosis451.2791605
Mean0.07982
Median Absolute Deviation (MAD)0
Skewness13.94272501
Sum3991
Variance0.1850124678
MonotonicityNot monotonic
2023-04-05T23:08:15.581075image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
5 39
 
0.1%
7 6
 
< 0.1%
6 5
 
< 0.1%
8 3
 
< 0.1%
10 2
 
< 0.1%
Other values (3) 4
 
< 0.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
17 2
< 0.1%
10 2
< 0.1%
8 3
< 0.1%

Electronics_6m
Real number (ℝ)

Distinct51
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.28572
Minimum0
Maximum133
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.644599image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum133
Range133
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.000290505
Coefficient of variation (CV)3.111323232
Kurtosis328.1721715
Mean1.28572
Median Absolute Deviation (MAD)0
Skewness13.51461061
Sum64286
Variance16.00232413
MonotonicityNot monotonic
2023-04-05T23:08:15.719164image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
5 826
 
1.7%
6 600
 
1.2%
7 412
 
0.8%
8 389
 
0.8%
9 274
 
0.5%
Other values (41) 1331
 
2.7%
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
ValueCountFrequency (%)
133 9
< 0.1%
131 1
 
< 0.1%
87 2
 
< 0.1%
85 4
 
< 0.1%
82 13
< 0.1%

MusicStores_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04938
Minimum0
Maximum163
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.782358image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum163
Range163
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.715948864
Coefficient of variation (CV)34.74987575
Kurtosis8177.573029
Mean0.04938
Median Absolute Deviation (MAD)0
Skewness87.28925641
Sum2469
Variance2.944480505
MonotonicityNot monotonic
2023-04-05T23:08:15.837487image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
5 25
 
0.1%
9 9
 
< 0.1%
6 9
 
< 0.1%
14 8
 
< 0.1%
24 6
 
< 0.1%
Other values (8) 18
 
< 0.1%
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
ValueCountFrequency (%)
163 5
< 0.1%
65 1
 
< 0.1%
24 6
< 0.1%
17 2
 
< 0.1%
15 1
 
< 0.1%

Restaurants_6m
Real number (ℝ)

Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9884
Minimum0
Maximum211
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:15.912401image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile22
Maximum211
Range211
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.36514226
Coefficient of variation (CV)2.077849063
Kurtosis43.35942087
Mean4.9884
Median Absolute Deviation (MAD)1
Skewness5.114187663
Sum249420
Variance107.4361742
MonotonicityNot monotonic
2023-04-05T23:08:15.981285image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
5 1787
 
3.6%
6 1459
 
2.9%
7 1278
 
2.6%
8 1090
 
2.2%
9 908
 
1.8%
Other values (106) 7539
 
15.1%
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
ValueCountFrequency (%)
211 1
 
< 0.1%
201 1
 
< 0.1%
196 3
< 0.1%
161 1
 
< 0.1%
150 5
< 0.1%

DigitalGoods_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56234
Minimum0
Maximum184
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.140036image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum184
Range184
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.329892456
Coefficient of variation (CV)7.699776748
Kurtosis697.1504599
Mean0.56234
Median Absolute Deviation (MAD)0
Skewness22.67581288
Sum28117
Variance18.74796868
MonotonicityNot monotonic
2023-04-05T23:08:16.211746image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
5 213
 
0.4%
6 126
 
0.3%
7 119
 
0.2%
9 111
 
0.2%
10 69
 
0.1%
Other values (43) 517
 
1.0%
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
ValueCountFrequency (%)
184 5
< 0.1%
137 7
< 0.1%
128 8
< 0.1%
121 6
< 0.1%
80 6
< 0.1%

Alcohol_6m
Real number (ℝ)

Distinct44
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40314
Minimum0
Maximum105
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.288585image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum105
Range105
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.003411693
Coefficient of variation (CV)4.969518513
Kurtosis661.1060958
Mean0.40314
Median Absolute Deviation (MAD)0
Skewness18.19384547
Sum20157
Variance4.013658414
MonotonicityNot monotonic
2023-04-05T23:08:16.360367image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
5 234
 
0.5%
6 183
 
0.4%
7 129
 
0.3%
8 102
 
0.2%
10 62
 
0.1%
Other values (34) 364
 
0.7%
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
ValueCountFrequency (%)
105 3
< 0.1%
91 1
 
< 0.1%
78 1
 
< 0.1%
50 1
 
< 0.1%
47 2
< 0.1%

Books_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15562
Minimum0
Maximum102
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.426092image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum102
Range102
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.165654147
Coefficient of variation (CV)7.490387785
Kurtosis4749.355926
Mean0.15562
Median Absolute Deviation (MAD)0
Skewness57.77552351
Sum7781
Variance1.358749591
MonotonicityNot monotonic
2023-04-05T23:08:16.484614image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
5 46
 
0.1%
7 31
 
0.1%
6 23
 
< 0.1%
8 9
 
< 0.1%
24 6
 
< 0.1%
Other values (9) 27
 
0.1%
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
ValueCountFrequency (%)
102 4
< 0.1%
34 2
 
< 0.1%
27 6
< 0.1%
24 6
< 0.1%
15 4
< 0.1%

Jewelry_6m
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18356
Minimum0
Maximum44
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.542877image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum44
Range44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7054329728
Coefficient of variation (CV)3.84306479
Kurtosis636.7629954
Mean0.18356
Median Absolute Deviation (MAD)0
Skewness14.29820106
Sum9178
Variance0.4976356791
MonotonicityNot monotonic
2023-04-05T23:08:16.591977image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
5 74
 
0.1%
6 41
 
0.1%
7 12
 
< 0.1%
8 11
 
< 0.1%
9 9
 
< 0.1%
Other values (4) 17
 
< 0.1%
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
ValueCountFrequency (%)
44 2
 
< 0.1%
14 4
< 0.1%
11 2
 
< 0.1%
10 9
< 0.1%
9 9
< 0.1%

DirectM_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07514
Minimum0
Maximum35
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.646302image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4828857463
Coefficient of variation (CV)6.42648052
Kurtosis920.1343764
Mean0.07514
Median Absolute Deviation (MAD)0
Skewness21.74502737
Sum3757
Variance0.233178644
MonotonicityNot monotonic
2023-04-05T23:08:16.697532image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
7 18
 
< 0.1%
5 15
 
< 0.1%
6 13
 
< 0.1%
12 10
 
< 0.1%
14 5
 
< 0.1%
Other values (4) 10
 
< 0.1%
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
ValueCountFrequency (%)
35 1
 
< 0.1%
19 4
 
< 0.1%
14 5
< 0.1%
12 10
< 0.1%
11 1
 
< 0.1%

Cash_6m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.753202image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:16.796979image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00088
Minimum0
Maximum5
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.843612image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04426358306
Coefficient of variation (CV)50.2995262
Kurtosis7567.308021
Mean0.00088
Median Absolute Deviation (MAD)0
Skewness77.89338677
Sum44
Variance0.001959264785
MonotonicityNot monotonic
2023-04-05T23:08:16.893029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
1 26
 
0.1%
0 49969
99.9%

FS_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00138
Minimum0
Maximum1
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:16.941143image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03712308126
Coefficient of variation (CV)26.90078352
Kurtosis719.7111522
Mean0.00138
Median Absolute Deviation (MAD)0
Skewness26.86414644
Sum69
Variance0.001378123162
MonotonicityNot monotonic
2023-04-05T23:08:16.990430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
1 69
 
0.1%
0 49931
99.9%

RentPayments_6m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62926
Minimum0
Maximum13
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.040263image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.428710144
Coefficient of variation (CV)2.27046077
Kurtosis8.04876218
Mean0.62926
Median Absolute Deviation (MAD)0
Skewness2.738019177
Sum31463
Variance2.041212677
MonotonicityNot monotonic
2023-04-05T23:08:17.098148image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
5 733
 
1.5%
6 428
 
0.9%
7 325
 
0.7%
8 130
 
0.3%
9 64
 
0.1%
Other values (3) 21
 
< 0.1%
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
ValueCountFrequency (%)
13 1
 
< 0.1%
11 2
 
< 0.1%
10 18
 
< 0.1%
9 64
0.1%
8 130
0.3%

WalletLoad_6m
Real number (ℝ)

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9795
Minimum0
Maximum225
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.170197image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum225
Range225
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.473615989
Coefficient of variation (CV)4.567244501
Kurtosis569.5985459
Mean0.9795
Median Absolute Deviation (MAD)0
Skewness17.61054299
Sum48975
Variance20.01324001
MonotonicityNot monotonic
2023-04-05T23:08:17.238128image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
5 548
 
1.1%
6 411
 
0.8%
7 266
 
0.5%
9 223
 
0.4%
8 213
 
0.4%
Other values (63) 1105
 
2.2%
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
ValueCountFrequency (%)
225 2
< 0.1%
202 1
< 0.1%
184 1
< 0.1%
162 1
< 0.1%
144 2
< 0.1%

BusinessServ_6m
Real number (ℝ)

Distinct63
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.552
Minimum0
Maximum211
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.310682image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum211
Range211
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.539576675
Coefficient of variation (CV)3.569314868
Kurtosis404.4159115
Mean1.552
Median Absolute Deviation (MAD)0
Skewness16.30107829
Sum77600
Variance30.68690974
MonotonicityNot monotonic
2023-04-05T23:08:17.381318image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
5 986
 
2.0%
6 756
 
1.5%
7 505
 
1.0%
8 317
 
0.6%
9 225
 
0.4%
Other values (53) 1153
 
2.3%
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
ValueCountFrequency (%)
211 5
 
< 0.1%
149 4
 
< 0.1%
130 14
< 0.1%
114 4
 
< 0.1%
107 7
< 0.1%

ProfServ_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.23736
Minimum0
Maximum42
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.445718image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.442366749
Coefficient of variation (CV)6.076705212
Kurtosis543.1740231
Mean0.23736
Median Absolute Deviation (MAD)0
Skewness20.80803992
Sum11868
Variance2.080421839
MonotonicityNot monotonic
2023-04-05T23:08:17.502365image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
5 91
 
0.2%
40 34
 
0.1%
9 27
 
0.1%
8 26
 
0.1%
6 26
 
0.1%
Other values (16) 90
 
0.2%
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
ValueCountFrequency (%)
42 9
 
< 0.1%
40 34
0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
27 2
 
< 0.1%

Education_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.38266
Minimum0
Maximum95
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.564458image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum95
Range95
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.128558653
Coefficient of variation (CV)5.562532413
Kurtosis739.0244771
Mean0.38266
Median Absolute Deviation (MAD)0
Skewness22.97968228
Sum19133
Variance4.53076194
MonotonicityNot monotonic
2023-04-05T23:08:17.711759image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
5 176
 
0.4%
6 110
 
0.2%
7 48
 
0.1%
9 34
 
0.1%
8 28
 
0.1%
Other values (28) 168
 
0.3%
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
ValueCountFrequency (%)
95 1
 
< 0.1%
83 12
< 0.1%
44 6
< 0.1%
43 5
< 0.1%
42 8
< 0.1%

GovtServices_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.33948
Minimum0
Maximum1127
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.779657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum1127
Range1127
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.38762229
Coefficient of variation (CV)12.23431652
Kurtosis2880.094419
Mean1.33948
Median Absolute Deviation (MAD)0
Skewness47.9914472
Sum66974
Variance268.5541644
MonotonicityNot monotonic
2023-04-05T23:08:17.848295image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
5 547
 
1.1%
6 400
 
0.8%
7 319
 
0.6%
8 173
 
0.3%
9 139
 
0.3%
Other values (49) 808
 
1.6%
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
ValueCountFrequency (%)
1127 6
 
< 0.1%
390 33
0.1%
217 2
 
< 0.1%
171 1
 
< 0.1%
157 1
 
< 0.1%

Agri_amt_6m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:17.909949image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:17.954040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct235
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.2849898
Minimum0
Maximum440000
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.022439image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum440000
Range440000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6200.959492
Coefficient of variation (CV)28.14971414
Kurtosis2493.646558
Mean220.2849898
Median Absolute Deviation (MAD)0
Skewness45.61014742
Sum11014249.49
Variance38451898.63
MonotonicityNot monotonic
2023-04-05T23:08:18.091062image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49536
99.1%
199 18
 
< 0.1%
1000 9
 
< 0.1%
1299 9
 
< 0.1%
100000 8
 
< 0.1%
2800 8
 
< 0.1%
10000 7
 
< 0.1%
50000 7
 
< 0.1%
68355 6
 
< 0.1%
30000 6
 
< 0.1%
Other values (225) 386
 
0.8%
ValueCountFrequency (%)
0 49536
99.1%
10 1
 
< 0.1%
25 1
 
< 0.1%
50 6
 
< 0.1%
71.58 1
 
< 0.1%
ValueCountFrequency (%)
440000 1
< 0.1%
405200 1
< 0.1%
400000 1
< 0.1%
395000 1
< 0.1%
380000 1
< 0.1%

Airline_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1492
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4669.319054
Minimum0
Maximum2694664
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.166139image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3919.5
Maximum2694664
Range2694664
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55460.76836
Coefficient of variation (CV)11.87769945
Kurtosis1166.967589
Mean4669.319054
Median Absolute Deviation (MAD)0
Skewness30.18308024
Sum233465952.7
Variance3075896827
MonotonicityNot monotonic
2023-04-05T23:08:18.241849image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46359
92.7%
150 72
 
0.1%
300 66
 
0.1%
250 60
 
0.1%
200 52
 
0.1%
100 44
 
0.1%
450 40
 
0.1%
170811 33
 
0.1%
400 31
 
0.1%
350 28
 
0.1%
Other values (1482) 3215
 
6.4%
ValueCountFrequency (%)
0 46359
92.7%
50 2
 
< 0.1%
99 3
 
< 0.1%
100 44
 
0.1%
104.25 2
 
< 0.1%
ValueCountFrequency (%)
2694664 2
 
< 0.1%
2444185.67 8
< 0.1%
2417315 1
 
< 0.1%
2088682 2
 
< 0.1%
1972827 2
 
< 0.1%

transport_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6259
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6478.121951
Minimum0
Maximum2169027.5
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.320843image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24000
Maximum2169027.5
Range2169027.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47412.96853
Coefficient of variation (CV)7.318937323
Kurtosis561.0998448
Mean6478.121951
Median Absolute Deviation (MAD)0
Skewness20.68576257
Sum323906097.6
Variance2247989585
MonotonicityNot monotonic
2023-04-05T23:08:18.395739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
2 221
 
0.4%
1000 117
 
0.2%
500 77
 
0.2%
1 65
 
0.1%
2000 53
 
0.1%
200 45
 
0.1%
1500 43
 
0.1%
300 34
 
0.1%
4 33
 
0.1%
Other values (6249) 11742
 
23.5%
ValueCountFrequency (%)
0 37570
75.1%
1 65
 
0.1%
1.3 1
 
< 0.1%
2 221
 
0.4%
2.8 1
 
< 0.1%
ValueCountFrequency (%)
2169027.5 1
 
< 0.1%
1403342.66 25
0.1%
1150000 6
 
< 0.1%
1027529.2 1
 
< 0.1%
1019060 1
 
< 0.1%

Insurance_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6348
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9789.220463
Minimum0
Maximum4484200
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.476000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42734.95
Maximum4484200
Range4484200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation70123.11161
Coefficient of variation (CV)7.163298843
Kurtosis1813.36226
Mean9789.220463
Median Absolute Deviation (MAD)0
Skewness34.35284618
Sum489461023.2
Variance4917250782
MonotonicityNot monotonic
2023-04-05T23:08:18.547406image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39445
78.9%
1116060 33
 
0.1%
530 33
 
0.1%
10000 27
 
0.1%
15000 26
 
0.1%
5000 26
 
0.1%
3801 21
 
< 0.1%
102250 20
 
< 0.1%
887 20
 
< 0.1%
52250 18
 
< 0.1%
Other values (6338) 10331
 
20.7%
ValueCountFrequency (%)
0 39445
78.9%
1 1
 
< 0.1%
2 5
 
< 0.1%
11 1
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
4484200 1
 
< 0.1%
4275963 5
< 0.1%
2176772.64 2
 
< 0.1%
1486353.22 1
 
< 0.1%
1329325.26 4
< 0.1%

Hotels_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6237
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6508.666604
Minimum0
Maximum4479268.69
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.620249image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3356
95-th percentile25603.06
Maximum4479268.69
Range4479268.69
Interquartile range (IQR)356

Descriptive statistics

Standard deviation49810.4365
Coefficient of variation (CV)7.65294023
Kurtosis3040.056778
Mean6508.666604
Median Absolute Deviation (MAD)0
Skewness42.77689715
Sum325433330.2
Variance2481079584
MonotonicityNot monotonic
2023-04-05T23:08:18.692482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36891
73.8%
3000 48
 
0.1%
2000 43
 
0.1%
1760 34
 
0.1%
1500 30
 
0.1%
5000 29
 
0.1%
10000 29
 
0.1%
1000 26
 
0.1%
4000 26
 
0.1%
2500 25
 
0.1%
Other values (6227) 12819
 
25.6%
ValueCountFrequency (%)
0 36891
73.8%
1 4
 
< 0.1%
2 18
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
4479268.69 2
 
< 0.1%
2260639.29 2
 
< 0.1%
1723207.74 7
< 0.1%
1576184.34 2
 
< 0.1%
1027180.5 4
< 0.1%

Railways_amt_6m
Real number (ℝ)

Distinct6459
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5483.707647
Minimum0
Maximum1080511
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.764282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile22424.38
Maximum1080511
Range1080511
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32094.90815
Coefficient of variation (CV)5.852775206
Kurtosis295.10659
Mean5483.707647
Median Absolute Deviation (MAD)0
Skewness14.74147247
Sum274185382.4
Variance1030083129
MonotonicityNot monotonic
2023-04-05T23:08:18.839063image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39278
78.6%
500 45
 
0.1%
3897 33
 
0.1%
200 30
 
0.1%
300 29
 
0.1%
102.12 27
 
0.1%
57457.7 25
 
0.1%
100 24
 
< 0.1%
644062.26 20
 
< 0.1%
1 18
 
< 0.1%
Other values (6449) 10471
 
20.9%
ValueCountFrequency (%)
0 39278
78.6%
1 18
 
< 0.1%
1.21 1
 
< 0.1%
1.53 1
 
< 0.1%
2 4
 
< 0.1%
ValueCountFrequency (%)
1080511 2
 
< 0.1%
820633.41 11
< 0.1%
785491 2
 
< 0.1%
783356.6 1
 
< 0.1%
650000 2
 
< 0.1%

Airports_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.370073
Minimum0
Maximum14471.55
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:18.988934image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum14471.55
Range14471.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation190.1376108
Coefficient of variation (CV)43.50902394
Kurtosis2906.5728
Mean4.370073
Median Absolute Deviation (MAD)0
Skewness52.14727746
Sum218503.65
Variance36152.31103
MonotonicityNot monotonic
2023-04-05T23:08:19.048213image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 49945
99.9%
10300 12
 
< 0.1%
750 5
 
< 0.1%
150 3
 
< 0.1%
600 3
 
< 0.1%
1500 3
 
< 0.1%
5200 3
 
< 0.1%
500 2
 
< 0.1%
2175.53 2
 
< 0.1%
1920 2
 
< 0.1%
Other values (17) 20
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
121.09 1
 
< 0.1%
130 1
 
< 0.1%
150 3
 
< 0.1%
240 1
 
< 0.1%
ValueCountFrequency (%)
14471.55 1
 
< 0.1%
10300 12
< 0.1%
8732.42 1
 
< 0.1%
6195 1
 
< 0.1%
5200 3
 
< 0.1%

Utility_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14777
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20979.84211
Minimum0
Maximum4087763.19
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.128007image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median984.6
Q37823.165
95-th percentile67000
Maximum4087763.19
Range4087763.19
Interquartile range (IQR)7823.165

Descriptive statistics

Standard deviation141481.9163
Coefficient of variation (CV)6.743707393
Kurtosis547.0708129
Mean20979.84211
Median Absolute Deviation (MAD)984.6
Skewness21.14555362
Sum1048992105
Variance2.001713264 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:19.207773image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
2 204
 
0.4%
1947 149
 
0.3%
1178.82 139
 
0.3%
666 132
 
0.3%
2999 110
 
0.2%
597 94
 
0.2%
4000 84
 
0.2%
719 80
 
0.2%
1298 67
 
0.1%
Other values (14767) 28253
56.5%
ValueCountFrequency (%)
0 20688
41.4%
1 10
 
< 0.1%
1.18 1
 
< 0.1%
1.5 1
 
< 0.1%
2 204
 
0.4%
ValueCountFrequency (%)
4087763.19 34
0.1%
3293669.12 3
 
< 0.1%
2983747.64 14
< 0.1%
2179970.74 2
 
< 0.1%
2135000 2
 
< 0.1%

Retail_amt_6m
Real number (ℝ)

Distinct11163
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10277.3661
Minimum0
Maximum2444657.25
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.289950image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34815.2775
95-th percentile40845.3
Maximum2444657.25
Range2444657.25
Interquartile range (IQR)4815.2775

Descriptive statistics

Standard deviation49404.26127
Coefficient of variation (CV)4.807093645
Kurtosis477.3922902
Mean10277.3661
Median Absolute Deviation (MAD)0
Skewness17.10848078
Sum513868305.1
Variance2440781032
MonotonicityNot monotonic
2023-04-05T23:08:19.369293image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
4000 155
 
0.3%
5000 88
 
0.2%
1000 88
 
0.2%
500 83
 
0.2%
2000 75
 
0.1%
10000 71
 
0.1%
300 56
 
0.1%
3000 55
 
0.1%
2500 48
 
0.1%
Other values (11153) 23556
47.1%
ValueCountFrequency (%)
0 25725
51.4%
1 10
 
< 0.1%
2 47
 
0.1%
3 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
2444657.25 1
 
< 0.1%
2028399.4 1
 
< 0.1%
1950777.21 1
 
< 0.1%
1700000 1
 
< 0.1%
1447823 11
< 0.1%

Medical_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct8057
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5956.067773
Minimum0
Maximum2402098
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.443314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31402
95-th percentile23824.6725
Maximum2402098
Range2402098
Interquartile range (IQR)1402

Descriptive statistics

Standard deviation37995.19547
Coefficient of variation (CV)6.379241626
Kurtosis1358.903652
Mean5956.067773
Median Absolute Deviation (MAD)0
Skewness28.47865804
Sum297803388.7
Variance1443634878
MonotonicityNot monotonic
2023-04-05T23:08:19.519114image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1000 88
 
0.2%
800 78
 
0.2%
600 76
 
0.2%
500 73
 
0.1%
400 66
 
0.1%
10000 62
 
0.1%
1500 60
 
0.1%
386 58
 
0.1%
Other values (8047) 16998
34.0%
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1.74 1
 
< 0.1%
2 16
 
< 0.1%
2.09 1
 
< 0.1%
ValueCountFrequency (%)
2402098 3
< 0.1%
1920000 2
< 0.1%
1200021 1
 
< 0.1%
1004101.15 2
< 0.1%
991851 3
< 0.1%

Fuel_amt_6m
Real number (ℝ)

Distinct15280
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7818.260737
Minimum0
Maximum720806.32
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.594005image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median957.51
Q38259.5975
95-th percentile34593.08
Maximum720806.32
Range720806.32
Interquartile range (IQR)8259.5975

Descriptive statistics

Standard deviation19450.44167
Coefficient of variation (CV)2.487822078
Kurtosis207.5981641
Mean7818.260737
Median Absolute Deviation (MAD)957.51
Skewness9.776964854
Sum390913036.8
Variance378319681.1
MonotonicityNot monotonic
2023-04-05T23:08:19.669389image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
2023.6 248
 
0.5%
3035.4 237
 
0.5%
2020 208
 
0.4%
1011.8 201
 
0.4%
1010 182
 
0.4%
505 153
 
0.3%
4047.2 128
 
0.3%
2529.5 100
 
0.2%
505.9 97
 
0.2%
Other values (15270) 26479
53.0%
ValueCountFrequency (%)
0 21967
43.9%
40.47 1
 
< 0.1%
41.36 2
 
< 0.1%
50.5 1
 
< 0.1%
70.7 1
 
< 0.1%
ValueCountFrequency (%)
720806.32 3
< 0.1%
642096.54 2
< 0.1%
457796.21 2
< 0.1%
301441.79 3
< 0.1%
280881.76 3
< 0.1%

DeptStores_amt_6m
Real number (ℝ)

Distinct16736
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11766.24459
Minimum0
Maximum2500871.5
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.748928image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1025.85
Q36647.36
95-th percentile30875.1925
Maximum2500871.5
Range2500871.5
Interquartile range (IQR)6647.36

Descriptive statistics

Standard deviation64171.46191
Coefficient of variation (CV)5.453860949
Kurtosis434.6925681
Mean11766.24459
Median Absolute Deviation (MAD)1025.85
Skewness17.05207472
Sum588312229.7
Variance4117976523
MonotonicityNot monotonic
2023-04-05T23:08:19.830924image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1000 50
 
0.1%
10000 43
 
0.1%
3889.84 34
 
0.1%
900 33
 
0.1%
17463.93 33
 
0.1%
200 31
 
0.1%
25000 29
 
0.1%
3000 27
 
0.1%
5000 27
 
0.1%
Other values (16726) 29334
58.7%
ValueCountFrequency (%)
0 20359
40.7%
1 6
 
< 0.1%
1.36 1
 
< 0.1%
2 1
 
< 0.1%
2.34 2
 
< 0.1%
ValueCountFrequency (%)
2500871.5 3
 
< 0.1%
2428372 1
 
< 0.1%
2059552.18 8
< 0.1%
1392592.48 4
< 0.1%
1307000 2
 
< 0.1%

Food_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5214
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1385.462862
Minimum0
Maximum1096500
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:19.911042image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3485
95-th percentile5079.79
Maximum1096500
Range1096500
Interquartile range (IQR)485

Descriptive statistics

Standard deviation14397.16652
Coefficient of variation (CV)10.39159325
Kurtosis3266.876924
Mean1385.462862
Median Absolute Deviation (MAD)0
Skewness49.93555124
Sum69273143.11
Variance207278403.8
MonotonicityNot monotonic
2023-04-05T23:08:19.986875image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34180
68.4%
2 92
 
0.2%
500 73
 
0.1%
400 57
 
0.1%
1000 50
 
0.1%
450 49
 
0.1%
200 47
 
0.1%
300 46
 
0.1%
480 46
 
0.1%
4 43
 
0.1%
Other values (5204) 15317
30.6%
ValueCountFrequency (%)
0 34180
68.4%
1 3
 
< 0.1%
2 92
 
0.2%
3.12 1
 
< 0.1%
4 43
 
0.1%
ValueCountFrequency (%)
1096500 2
 
< 0.1%
1046805 3
< 0.1%
539123 1
 
< 0.1%
521890 1
 
< 0.1%
488020 5
< 0.1%

Auto_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1867
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2167.957446
Minimum0
Maximum1219987
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.139662image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4747.1
Maximum1219987
Range1219987
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26685.79818
Coefficient of variation (CV)12.30918911
Kurtosis777.9184609
Mean2167.957446
Median Absolute Deviation (MAD)0
Skewness25.52549873
Sum108397872.3
Variance712131824.5
MonotonicityNot monotonic
2023-04-05T23:08:20.216836image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46021
92.0%
10000 56
 
0.1%
670267.04 33
 
0.1%
25000 29
 
0.1%
11000 27
 
0.1%
3000 25
 
0.1%
5000 24
 
< 0.1%
1000 23
 
< 0.1%
2000 21
 
< 0.1%
21000 21
 
< 0.1%
Other values (1857) 3720
 
7.4%
ValueCountFrequency (%)
0 46021
92.0%
59 2
 
< 0.1%
60 2
 
< 0.1%
66 1
 
< 0.1%
84 1
 
< 0.1%
ValueCountFrequency (%)
1219987 4
 
< 0.1%
802400 1
 
< 0.1%
800000 4
 
< 0.1%
709100 4
 
< 0.1%
670267.04 33
0.1%

ClothStores_amt_6m
Real number (ℝ)

Distinct12156
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9433.808793
Minimum0
Maximum1154700
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.291366image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median499
Q37897.24
95-th percentile39944.9
Maximum1154700
Range1154700
Interquartile range (IQR)7897.24

Descriptive statistics

Standard deviation31098.84787
Coefficient of variation (CV)3.296531502
Kurtosis291.5345429
Mean9433.808793
Median Absolute Deviation (MAD)499
Skewness13.04381894
Sum471690439.6
Variance967138338.6
MonotonicityNot monotonic
2023-04-05T23:08:20.365281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24277
48.6%
5000 54
 
0.1%
3000 52
 
0.1%
1000 49
 
0.1%
400 48
 
0.1%
2000 43
 
0.1%
1500 42
 
0.1%
1499 36
 
0.1%
599 34
 
0.1%
999 34
 
0.1%
Other values (12146) 25331
50.7%
ValueCountFrequency (%)
0 24277
48.6%
2 27
 
0.1%
3.1 1
 
< 0.1%
10 7
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1154700 3
< 0.1%
964208.44 3
< 0.1%
837031.06 4
< 0.1%
800000 1
 
< 0.1%
789448.5 1
 
< 0.1%

MiscServices_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5445
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2870.836041
Minimum0
Maximum1568000
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.445625image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3308
95-th percentile11139.15
Maximum1568000
Range1568000
Interquartile range (IQR)308

Descriptive statistics

Standard deviation21446.42166
Coefficient of variation (CV)7.470444621
Kurtosis1377.045698
Mean2870.836041
Median Absolute Deviation (MAD)0
Skewness30.16463497
Sum143541802.1
Variance459949002.1
MonotonicityNot monotonic
2023-04-05T23:08:20.524750image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
2 1374
 
2.7%
1000 73
 
0.1%
500 68
 
0.1%
600 64
 
0.1%
2000 60
 
0.1%
5000 56
 
0.1%
2500 53
 
0.1%
3000 52
 
0.1%
6000 51
 
0.1%
Other values (5435) 13364
 
26.7%
ValueCountFrequency (%)
0 34785
69.6%
1 10
 
< 0.1%
2 1374
 
2.7%
3 1
 
< 0.1%
4 11
 
< 0.1%
ValueCountFrequency (%)
1568000 1
< 0.1%
1105500 2
< 0.1%
1000705.7 2
< 0.1%
833000 2
< 0.1%
810929 2
< 0.1%

HomeF_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1244
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1107.691418
Minimum0
Maximum521180.38
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.604855image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile800
Maximum521180.38
Range521180.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11198.17701
Coefficient of variation (CV)10.10947348
Kurtosis961.430417
Mean1107.691418
Median Absolute Deviation (MAD)0
Skewness26.28062187
Sum55384570.89
Variance125399168.3
MonotonicityNot monotonic
2023-04-05T23:08:20.683904image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47285
94.6%
5000 32
 
0.1%
20000 25
 
0.1%
10000 21
 
< 0.1%
1000 16
 
< 0.1%
15000 13
 
< 0.1%
4200 13
 
< 0.1%
4449 12
 
< 0.1%
8000 12
 
< 0.1%
30000 12
 
< 0.1%
Other values (1234) 2559
 
5.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
90 1
 
< 0.1%
ValueCountFrequency (%)
521180.38 2
 
< 0.1%
516155 1
 
< 0.1%
500000 6
< 0.1%
387326 1
 
< 0.1%
353000 1
 
< 0.1%

Electronics_amt_6m
Real number (ℝ)

Distinct8450
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7785.50485
Minimum0
Maximum1075000
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.759731image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32105
95-th percentile36104.53
Maximum1075000
Range1075000
Interquartile range (IQR)2105

Descriptive statistics

Standard deviation37669.26346
Coefficient of variation (CV)4.838384175
Kurtosis260.1614027
Mean7785.50485
Median Absolute Deviation (MAD)0
Skewness13.72312102
Sum389275242.5
Variance1418973409
MonotonicityNot monotonic
2023-04-05T23:08:20.835851image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
199 103
 
0.2%
1499 57
 
0.1%
549 52
 
0.1%
299 50
 
0.1%
2 42
 
0.1%
10000 41
 
0.1%
2000 41
 
0.1%
2999 40
 
0.1%
15000 36
 
0.1%
Other values (8440) 17426
34.9%
ValueCountFrequency (%)
0 32112
64.2%
1 25
 
0.1%
2 42
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
1075000 1
 
< 0.1%
1004027.56 3
 
< 0.1%
959690 3
 
< 0.1%
942423 13
< 0.1%
790833.6 3
 
< 0.1%

MusicStores_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct246
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.767819
Minimum0
Maximum272142
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:20.911405image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum272142
Range272142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2954.615352
Coefficient of variation (CV)33.66399422
Kurtosis7219.326039
Mean87.767819
Median Absolute Deviation (MAD)0
Skewness80.00078775
Sum4388390.95
Variance8729751.876
MonotonicityNot monotonic
2023-04-05T23:08:20.987305image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49307
98.6%
99 22
 
< 0.1%
2000 18
 
< 0.1%
149 14
 
< 0.1%
5000 14
 
< 0.1%
75 13
 
< 0.1%
1499 13
 
< 0.1%
449 13
 
< 0.1%
269 12
 
< 0.1%
169 11
 
< 0.1%
Other values (236) 563
 
1.1%
ValueCountFrequency (%)
0 49307
98.6%
5 3
 
< 0.1%
7 1
 
< 0.1%
15 5
 
< 0.1%
18 4
 
< 0.1%
ValueCountFrequency (%)
272142 5
< 0.1%
88411 1
 
< 0.1%
50179 2
 
< 0.1%
49500 2
 
< 0.1%
39000 1
 
< 0.1%

Restaurants_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14564
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5916.247728
Minimum0
Maximum1020000
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.061021image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median680.1
Q34861
95-th percentile24971
Maximum1020000
Range1020000
Interquartile range (IQR)4861

Descriptive statistics

Standard deviation22675.5409
Coefficient of variation (CV)3.832757169
Kurtosis668.8097281
Mean5916.247728
Median Absolute Deviation (MAD)680.1
Skewness20.79086653
Sum295812386.4
Variance514180154.9
MonotonicityNot monotonic
2023-04-05T23:08:21.225718image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
2 399
 
0.8%
4 152
 
0.3%
300 42
 
0.1%
6 37
 
0.1%
2061.65 33
 
0.1%
220 32
 
0.1%
1000 32
 
0.1%
900 31
 
0.1%
400 30
 
0.1%
Other values (14554) 28958
57.9%
ValueCountFrequency (%)
0 20254
40.5%
1 4
 
< 0.1%
2 399
 
0.8%
4 152
 
0.3%
6 37
 
0.1%
ValueCountFrequency (%)
1020000 1
 
< 0.1%
1000000 1
 
< 0.1%
863465.05 9
< 0.1%
657847.38 7
< 0.1%
495000 1
 
< 0.1%

DigitalGoods_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1822
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2473.969376
Minimum0
Maximum948600
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.298584image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1891
Maximum948600
Range948600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30509.16017
Coefficient of variation (CV)12.33206865
Kurtosis531.4836965
Mean2473.969376
Median Absolute Deviation (MAD)0
Skewness21.24664222
Sum123698468.8
Variance930808854.4
MonotonicityNot monotonic
2023-04-05T23:08:21.369324image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
2 169
 
0.3%
1300 120
 
0.2%
390 112
 
0.2%
299 106
 
0.2%
200 84
 
0.2%
387 71
 
0.1%
20 64
 
0.1%
567 64
 
0.1%
258 55
 
0.1%
Other values (1812) 5112
 
10.2%
ValueCountFrequency (%)
0 44043
88.1%
1 42
 
0.1%
2 169
 
0.3%
4 14
 
< 0.1%
5 3
 
< 0.1%
ValueCountFrequency (%)
948600 8
 
< 0.1%
884000 2
 
< 0.1%
865000 20
< 0.1%
811681.72 2
 
< 0.1%
602499 5
 
< 0.1%

Alcohol_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2019
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean797.6000446
Minimum0
Maximum399994
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.449019image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3683
Maximum399994
Range399994
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6130.755373
Coefficient of variation (CV)7.686503297
Kurtosis1671.293833
Mean797.6000446
Median Absolute Deviation (MAD)0
Skewness32.97707862
Sum39880002.23
Variance37586161.44
MonotonicityNot monotonic
2023-04-05T23:08:21.527179image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43436
86.9%
900 48
 
0.1%
600 47
 
0.1%
360 42
 
0.1%
1200 34
 
0.1%
400 34
 
0.1%
800 31
 
0.1%
720 30
 
0.1%
300 30
 
0.1%
540 30
 
0.1%
Other values (2009) 6238
 
12.5%
ValueCountFrequency (%)
0 43436
86.9%
60 1
 
< 0.1%
90 4
 
< 0.1%
104 1
 
< 0.1%
105 2
 
< 0.1%
ValueCountFrequency (%)
399994 2
< 0.1%
390730 1
 
< 0.1%
390635 1
 
< 0.1%
231400 2
< 0.1%
200240 3
< 0.1%

Books_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1938
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634.0098318
Minimum0
Maximum949000
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.609601image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1526
Maximum949000
Range949000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10100.5045
Coefficient of variation (CV)15.93114805
Kurtosis3809.320487
Mean634.0098318
Median Absolute Deviation (MAD)0
Skewness52.38559939
Sum31700491.59
Variance102020191.1
MonotonicityNot monotonic
2023-04-05T23:08:21.680645image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45427
90.9%
450 25
 
0.1%
400 22
 
< 0.1%
300 22
 
< 0.1%
40000 20
 
< 0.1%
900 19
 
< 0.1%
1000 18
 
< 0.1%
2500 18
 
< 0.1%
600 17
 
< 0.1%
1700 17
 
< 0.1%
Other values (1928) 4395
 
8.8%
ValueCountFrequency (%)
0 45427
90.9%
1 3
 
< 0.1%
1.51 1
 
< 0.1%
8 2
 
< 0.1%
10 5
 
< 0.1%
ValueCountFrequency (%)
949000 2
 
< 0.1%
464107.59 4
< 0.1%
400000 1
 
< 0.1%
368130 6
< 0.1%
281550 1
 
< 0.1%

Jewelry_amt_6m
Real number (ℝ)

Distinct2303
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5020.164728
Minimum0
Maximum1312235
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.754216image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20387.2
Maximum1312235
Range1312235
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31291.24714
Coefficient of variation (CV)6.233111628
Kurtosis274.1977494
Mean5020.164728
Median Absolute Deviation (MAD)0
Skewness13.52489059
Sum251008236.4
Variance979142147.6
MonotonicityNot monotonic
2023-04-05T23:08:21.832291image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44421
88.8%
10000 105
 
0.2%
5000 78
 
0.2%
20000 76
 
0.2%
30000 53
 
0.1%
6000 51
 
0.1%
2000 51
 
0.1%
4000 45
 
0.1%
15000 41
 
0.1%
50000 38
 
0.1%
Other values (2293) 5041
 
10.1%
ValueCountFrequency (%)
0 44421
88.8%
10 2
 
< 0.1%
110 1
 
< 0.1%
119 3
 
< 0.1%
120 1
 
< 0.1%
ValueCountFrequency (%)
1312235 1
< 0.1%
1126230 1
< 0.1%
832650 2
< 0.1%
829200 2
< 0.1%
724000 1
< 0.1%

DirectM_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct836
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440.4139112
Minimum0
Maximum1839140.65
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:21.910760image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile149
Maximum1839140.65
Range1839140.65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16126.08507
Coefficient of variation (CV)36.61574865
Kurtosis10640.73601
Mean440.4139112
Median Absolute Deviation (MAD)0
Skewness97.61371505
Sum22020695.56
Variance260050619.8
MonotonicityNot monotonic
2023-04-05T23:08:21.986832image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47389
94.8%
199 390
 
0.8%
649 338
 
0.7%
499 169
 
0.3%
149 115
 
0.2%
398 29
 
0.1%
2 26
 
0.1%
1298 19
 
< 0.1%
998 15
 
< 0.1%
501 11
 
< 0.1%
Other values (826) 1499
 
3.0%
ValueCountFrequency (%)
0 47389
94.8%
1 1
 
< 0.1%
2 26
 
0.1%
12 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
1839140.65 3
< 0.1%
1115580.42 1
 
< 0.1%
516502.12 1
 
< 0.1%
351866.94 1
 
< 0.1%
330896.88 1
 
< 0.1%

Cash_amt_6m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.051417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:22.095396image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.913654
Minimum0
Maximum149644.47
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.146128image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum149644.47
Range149644.47
Interquartile range (IQR)0

Descriptive statistics

Standard deviation967.3857349
Coefficient of variation (CV)108.5285266
Kurtosis22921.57892
Mean8.913654
Median Absolute Deviation (MAD)0
Skewness148.9790539
Sum445682.7
Variance935835.1601
MonotonicityNot monotonic
2023-04-05T23:08:22.282680image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
3393.16 4
 
< 0.1%
4457.23 4
 
< 0.1%
5007.12 3
 
< 0.1%
319.01 2
 
< 0.1%
149644.47 2
 
< 0.1%
21072.71 2
 
< 0.1%
2399.01 1
 
< 0.1%
8469.32 1
 
< 0.1%
Other values (7) 7
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
319.01 2
 
< 0.1%
754.41 1
 
< 0.1%
2009.57 1
 
< 0.1%
ValueCountFrequency (%)
149644.47 2
< 0.1%
27988.24 1
< 0.1%
21072.71 2
< 0.1%
8469.32 1
< 0.1%
5013.32 1
< 0.1%

FS_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.366
Minimum0
Maximum30000
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.337793image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30000
Range30000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation174.5065703
Coefficient of variation (CV)127.7500515
Kurtosis25755.09187
Mean1.366
Median Absolute Deviation (MAD)0
Skewness159.7054686
Sum68300
Variance30452.54309
MonotonicityNot monotonic
2023-04-05T23:08:22.385132image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
30000 1
 
< 0.1%
24900 1
 
< 0.1%
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
24900 1
 
< 0.1%
30000 1
 
< 0.1%
ValueCountFrequency (%)
30000 1
 
< 0.1%
24900 1
 
< 0.1%
200 67
 
0.1%
0 49931
99.9%

RentPayments_amt_6m
Real number (ℝ)

Distinct6705
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17250.93866
Minimum0
Maximum1013828
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.454239image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile106470.675
Maximum1013828
Range1013828
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51878.21575
Coefficient of variation (CV)3.007269156
Kurtosis42.62888392
Mean17250.93866
Median Absolute Deviation (MAD)0
Skewness5.359033025
Sum862546933
Variance2691349269
MonotonicityNot monotonic
2023-04-05T23:08:22.532850image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38583
77.2%
20300 65
 
0.1%
10150 58
 
0.1%
3540 57
 
0.1%
25375 42
 
0.1%
20200 40
 
0.1%
40600 30
 
0.1%
30420 28
 
0.1%
20310 27
 
0.1%
30300 25
 
0.1%
Other values (6695) 11045
 
22.1%
ValueCountFrequency (%)
0 38583
77.2%
1 1
 
< 0.1%
1.01 1
 
< 0.1%
2 18
 
< 0.1%
5.11 1
 
< 0.1%
ValueCountFrequency (%)
1013828 1
< 0.1%
959020 1
< 0.1%
891620.5 1
< 0.1%
807058 1
< 0.1%
797900 2
< 0.1%

WalletLoad_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4467
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3405.023854
Minimum0
Maximum1835364.3
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.610471image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20336.72
Maximum1835364.3
Range1835364.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20662.81433
Coefficient of variation (CV)6.06833174
Kurtosis2728.405834
Mean3405.023854
Median Absolute Deviation (MAD)0
Skewness38.26647813
Sum170251192.7
Variance426951896
MonotonicityNot monotonic
2023-04-05T23:08:22.686900image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1023 139
 
0.3%
1000 123
 
0.2%
500 105
 
0.2%
2000 103
 
0.2%
4000 103
 
0.2%
10230 99
 
0.2%
2046 85
 
0.2%
5115 81
 
0.2%
20460 79
 
0.2%
Other values (4457) 9634
 
19.3%
ValueCountFrequency (%)
0 39449
78.9%
1 5
 
< 0.1%
1.02 5
 
< 0.1%
1.03 1
 
< 0.1%
2 43
 
0.1%
ValueCountFrequency (%)
1835364.3 2
 
< 0.1%
684317.7 4
< 0.1%
656226.57 6
< 0.1%
337932 7
< 0.1%
323330 2
 
< 0.1%

BusinessServ_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct10073
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10236.93259
Minimum0
Maximum4905650
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.767610image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31399
95-th percentile20072
Maximum4905650
Range4905650
Interquartile range (IQR)1399

Descriptive statistics

Standard deviation110315.3813
Coefficient of variation (CV)10.77621449
Kurtosis1051.347246
Mean10236.93259
Median Absolute Deviation (MAD)0
Skewness28.70445734
Sum511846629.6
Variance1.216948335 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:22.846281image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1000 94
 
0.2%
600 65
 
0.1%
899 63
 
0.1%
1500 63
 
0.1%
1499 60
 
0.1%
500 56
 
0.1%
2 49
 
0.1%
400 48
 
0.1%
3000 45
 
0.1%
Other values (10063) 20484
41.0%
ValueCountFrequency (%)
0 28973
57.9%
1 17
 
< 0.1%
2 49
 
0.1%
3 1
 
< 0.1%
4 9
 
< 0.1%
ValueCountFrequency (%)
4905650 11
< 0.1%
3121264.01 1
 
< 0.1%
2828574 14
< 0.1%
2697100 4
 
< 0.1%
1894211.09 12
< 0.1%

ProfServ_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2179
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2725.70208
Minimum0
Maximum1500000
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:22.922323image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6807.2
Maximum1500000
Range1500000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27657.61293
Coefficient of variation (CV)10.14696842
Kurtosis1000.913767
Mean2725.70208
Median Absolute Deviation (MAD)0
Skewness26.89576097
Sum136285104
Variance764943553.1
MonotonicityNot monotonic
2023-04-05T23:08:22.997698image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44022
88.0%
500 95
 
0.2%
1000 76
 
0.2%
1500 68
 
0.1%
3000 66
 
0.1%
5000 65
 
0.1%
10000 61
 
0.1%
4032 52
 
0.1%
2000 50
 
0.1%
400 40
 
0.1%
Other values (2169) 5405
 
10.8%
ValueCountFrequency (%)
0 44022
88.0%
1 8
 
< 0.1%
10 3
 
< 0.1%
29 2
 
< 0.1%
31 1
 
< 0.1%
ValueCountFrequency (%)
1500000 2
< 0.1%
1302900 2
< 0.1%
1300000 1
< 0.1%
1150000 1
< 0.1%
1125000 1
< 0.1%

Education_amt_6m
Real number (ℝ)

Distinct3859
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6434.501254
Minimum0
Maximum1505584
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.079228image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile34443.63
Maximum1505584
Range1505584
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37406.22845
Coefficient of variation (CV)5.813384281
Kurtosis451.9611095
Mean6434.501254
Median Absolute Deviation (MAD)0
Skewness17.12044735
Sum321725062.7
Variance1399225926
MonotonicityNot monotonic
2023-04-05T23:08:23.154089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41554
83.1%
2 572
 
1.1%
455 41
 
0.1%
1000 40
 
0.1%
10000 39
 
0.1%
500 37
 
0.1%
15000 35
 
0.1%
68215.44 33
 
0.1%
3000 31
 
0.1%
20000 30
 
0.1%
Other values (3849) 7588
 
15.2%
ValueCountFrequency (%)
0 41554
83.1%
1 1
 
< 0.1%
1.03 1
 
< 0.1%
2 572
 
1.1%
3 1
 
< 0.1%
ValueCountFrequency (%)
1505584 3
< 0.1%
1250000 5
< 0.1%
1186450.01 3
< 0.1%
928098.23 1
 
< 0.1%
898741 6
< 0.1%

GovtServices_amt_6m
Real number (ℝ)

SKEWED  ZEROS 

Distinct7060
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18016.19656
Minimum0
Maximum15000000
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.235040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3300
95-th percentile25266.326
Maximum15000000
Range15000000
Interquartile range (IQR)300

Descriptive statistics

Standard deviation389880.2572
Coefficient of variation (CV)21.64054194
Kurtosis1436.625262
Mean18016.19656
Median Absolute Deviation (MAD)0
Skewness37.52586981
Sum900809827.8
Variance1.52006615 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:23.311141image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
50 113
 
0.2%
1526.55 92
 
0.2%
500 83
 
0.2%
201.76 70
 
0.1%
200 61
 
0.1%
100 53
 
0.1%
1000 45
 
0.1%
50445 43
 
0.1%
2000 41
 
0.1%
Other values (7050) 12826
 
25.7%
ValueCountFrequency (%)
0 36573
73.1%
3.03 2
 
< 0.1%
5.06 3
 
< 0.1%
7 1
 
< 0.1%
8.26 11
 
< 0.1%
ValueCountFrequency (%)
15000000 33
0.1%
2458136 5
 
< 0.1%
2281696.4 1
 
< 0.1%
1654514 1
 
< 0.1%
1594670.03 2
 
< 0.1%

Agri_12m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.375826image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:23.422645image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.01372
Minimum0
Maximum17
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.554479image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1941456037
Coefficient of variation (CV)14.15055421
Kurtosis2097.9857
Mean0.01372
Median Absolute Deviation (MAD)0
Skewness34.78914986
Sum686
Variance0.03769251545
MonotonicityNot monotonic
2023-04-05T23:08:23.604095image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
6 3
 
< 0.1%
5 3
 
< 0.1%
9 2
 
< 0.1%
7 1
 
< 0.1%
17 1
 
< 0.1%
ValueCountFrequency (%)
0 49536
99.1%
1 360
 
0.7%
2 56
 
0.1%
3 23
 
< 0.1%
4 14
 
< 0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
14 1
 
< 0.1%
9 2
< 0.1%
7 1
 
< 0.1%
6 3
< 0.1%

Airline_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct30
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22376
Minimum0
Maximum86
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.669126image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum86
Range86
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.227013842
Coefficient of variation (CV)9.952689678
Kurtosis1033.304052
Mean0.22376
Median Absolute Deviation (MAD)0
Skewness29.50974303
Sum11188
Variance4.959590654
MonotonicityNot monotonic
2023-04-05T23:08:23.730125image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
5 107
 
0.2%
6 59
 
0.1%
7 49
 
0.1%
10 38
 
0.1%
8 34
 
0.1%
Other values (20) 146
 
0.3%
ValueCountFrequency (%)
0 46359
92.7%
1 1963
 
3.9%
2 743
 
1.5%
3 353
 
0.7%
4 149
 
0.3%
ValueCountFrequency (%)
86 12
< 0.1%
80 14
< 0.1%
47 8
< 0.1%
38 2
 
< 0.1%
37 1
 
< 0.1%

transport_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.10542
Minimum0
Maximum199
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.800772image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum199
Range199
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.996150907
Coefficient of variation (CV)5.424319179
Kurtosis627.6198803
Mean1.10542
Median Absolute Deviation (MAD)0
Skewness21.19144641
Sum55271
Variance35.9538257
MonotonicityNot monotonic
2023-04-05T23:08:23.873191image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
5 448
 
0.9%
6 330
 
0.7%
7 249
 
0.5%
8 198
 
0.4%
9 136
 
0.3%
Other values (63) 1140
 
2.3%
ValueCountFrequency (%)
0 37570
75.1%
1 5482
 
11.0%
2 2432
 
4.9%
3 1270
 
2.5%
4 745
 
1.5%
ValueCountFrequency (%)
199 25
0.1%
148 1
 
< 0.1%
122 1
 
< 0.1%
120 2
 
< 0.1%
106 1
 
< 0.1%

Insurance_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct46
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57774
Minimum0
Maximum348
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:23.952398image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum348
Range348
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.488919636
Coefficient of variation (CV)7.769792011
Kurtosis3666.095835
Mean0.57774
Median Absolute Deviation (MAD)0
Skewness51.17353581
Sum28887
Variance20.1503995
MonotonicityNot monotonic
2023-04-05T23:08:24.028001image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
5 177
 
0.4%
6 119
 
0.2%
7 78
 
0.2%
12 42
 
0.1%
34 40
 
0.1%
Other values (36) 369
 
0.7%
ValueCountFrequency (%)
0 39445
78.9%
1 6145
 
12.3%
2 2214
 
4.4%
3 928
 
1.9%
4 443
 
0.9%
ValueCountFrequency (%)
348 5
< 0.1%
94 9
< 0.1%
91 7
< 0.1%
89 3
 
< 0.1%
73 2
 
< 0.1%

Hotels_12m
Real number (ℝ)

Distinct33
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72448
Minimum0
Maximum65
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.099528image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum65
Range65
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.03482961
Coefficient of variation (CV)2.808676029
Kurtosis156.4901343
Mean0.72448
Median Absolute Deviation (MAD)0
Skewness8.30915014
Sum36224
Variance4.14053154
MonotonicityNot monotonic
2023-04-05T23:08:24.158806image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
5 569
 
1.1%
6 395
 
0.8%
7 281
 
0.6%
8 222
 
0.4%
10 119
 
0.2%
Other values (23) 452
 
0.9%
ValueCountFrequency (%)
0 36891
73.8%
1 5807
 
11.6%
2 2897
 
5.8%
3 1494
 
3.0%
4 873
 
1.7%
ValueCountFrequency (%)
65 6
< 0.1%
38 3
< 0.1%
36 1
 
< 0.1%
31 2
 
< 0.1%
29 3
< 0.1%

Railways_12m
Real number (ℝ)

Distinct45
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72686
Minimum0
Maximum88
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.228532image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum88
Range88
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.135737744
Coefficient of variation (CV)4.314087642
Kurtosis341.1364602
Mean0.72686
Median Absolute Deviation (MAD)0
Skewness15.25758491
Sum36343
Variance9.832851197
MonotonicityNot monotonic
2023-04-05T23:08:24.296898image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
5 388
 
0.8%
6 313
 
0.6%
7 208
 
0.4%
8 180
 
0.4%
10 155
 
0.3%
Other values (35) 627
 
1.3%
ValueCountFrequency (%)
0 39278
78.6%
1 4539
 
9.1%
2 2330
 
4.7%
3 1261
 
2.5%
4 721
 
1.4%
ValueCountFrequency (%)
88 20
< 0.1%
80 1
 
< 0.1%
67 10
< 0.1%
65 2
 
< 0.1%
61 4
 
< 0.1%

Airports_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00146
Minimum0
Maximum5
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.352384image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04917231699
Coefficient of variation (CV)33.67966917
Kurtosis3033.124738
Mean0.00146
Median Absolute Deviation (MAD)0
Skewness46.50959616
Sum73
Variance0.002417916758
MonotonicityNot monotonic
2023-04-05T23:08:24.402318image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
1 40
 
0.1%
2 14
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
2 14
 
< 0.1%
1 40
 
0.1%
0 49945
99.9%

Utility_12m
Real number (ℝ)

Distinct90
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5979
Minimum0
Maximum389
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.472490image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile13
Maximum389
Range389
Interquartile range (IQR)4

Descriptive statistics

Standard deviation13.89091627
Coefficient of variation (CV)3.860840009
Kurtosis489.6128409
Mean3.5979
Median Absolute Deviation (MAD)1
Skewness19.79756961
Sum179895
Variance192.9575547
MonotonicityNot monotonic
2023-04-05T23:08:24.549456image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
5 2048
 
4.1%
6 1642
 
3.3%
7 1255
 
2.5%
8 891
 
1.8%
9 832
 
1.7%
Other values (80) 4042
 
8.1%
ValueCountFrequency (%)
0 20688
41.4%
1 7710
 
15.4%
2 4609
 
9.2%
3 3598
 
7.2%
4 2685
 
5.4%
ValueCountFrequency (%)
389 34
0.1%
285 19
< 0.1%
274 1
 
< 0.1%
269 4
 
< 0.1%
176 14
< 0.1%

Retail_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct71
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.84948
Minimum0
Maximum1044
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.630297image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile7
Maximum1044
Range1044
Interquartile range (IQR)2

Descriptive statistics

Standard deviation9.256715263
Coefficient of variation (CV)5.005036693
Kurtosis4258.902872
Mean1.84948
Median Absolute Deviation (MAD)0
Skewness52.81860742
Sum92474
Variance85.68677747
MonotonicityNot monotonic
2023-04-05T23:08:24.705339image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
5 1258
 
2.5%
6 838
 
1.7%
7 675
 
1.4%
8 441
 
0.9%
9 401
 
0.8%
Other values (61) 1420
 
2.8%
ValueCountFrequency (%)
0 25725
51.4%
1 9248
 
18.5%
2 5028
 
10.1%
3 3046
 
6.1%
4 1920
 
3.8%
ValueCountFrequency (%)
1044 1
 
< 0.1%
470 2
 
< 0.1%
465 3
< 0.1%
378 2
 
< 0.1%
369 5
< 0.1%

Medical_12m
Real number (ℝ)

Distinct52
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.43778
Minimum0
Maximum83
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:24.864403image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile7
Maximum83
Range83
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.608189165
Coefficient of variation (CV)2.509555819
Kurtosis71.74185192
Mean1.43778
Median Absolute Deviation (MAD)0
Skewness6.334131441
Sum71889
Variance13.01902905
MonotonicityNot monotonic
2023-04-05T23:08:24.932308image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
5 1018
 
2.0%
6 752
 
1.5%
7 616
 
1.2%
8 470
 
0.9%
9 318
 
0.6%
Other values (42) 1617
 
3.2%
ValueCountFrequency (%)
0 32314
64.6%
1 5870
 
11.7%
2 3410
 
6.8%
3 2137
 
4.3%
4 1478
 
3.0%
ValueCountFrequency (%)
83 4
< 0.1%
65 3
 
< 0.1%
61 8
< 0.1%
58 4
< 0.1%
54 5
< 0.1%

Fuel_12m
Real number (ℝ)

Distinct77
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.47412
Minimum0
Maximum193
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.007078image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile14
Maximum193
Range193
Interquartile range (IQR)5

Descriptive statistics

Standard deviation6.213805795
Coefficient of variation (CV)1.788598492
Kurtosis65.06113242
Mean3.47412
Median Absolute Deviation (MAD)1
Skewness5.34325986
Sum173706
Variance38.61138245
MonotonicityNot monotonic
2023-04-05T23:08:25.084494image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
5 2121
 
4.2%
6 1802
 
3.6%
7 1399
 
2.8%
8 1208
 
2.4%
9 1095
 
2.2%
Other values (67) 5362
 
10.7%
ValueCountFrequency (%)
0 21967
43.9%
1 5535
 
11.1%
2 3807
 
7.6%
3 3078
 
6.2%
4 2626
 
5.3%
ValueCountFrequency (%)
193 1
 
< 0.1%
138 3
< 0.1%
112 1
 
< 0.1%
110 4
< 0.1%
96 1
 
< 0.1%

DeptStores_12m
Real number (ℝ)

Distinct92
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.76012
Minimum0
Maximum187
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.165013image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile16
Maximum187
Range187
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.832164735
Coefficient of variation (CV)2.082956059
Kurtosis65.82871473
Mean3.76012
Median Absolute Deviation (MAD)1
Skewness6.028340139
Sum188006
Variance61.34280444
MonotonicityNot monotonic
2023-04-05T23:08:25.240855image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
5 1889
 
3.8%
6 1340
 
2.7%
7 1108
 
2.2%
8 943
 
1.9%
9 814
 
1.6%
Other values (82) 5430
 
10.9%
ValueCountFrequency (%)
0 20359
40.7%
1 7343
 
14.7%
2 4793
 
9.6%
3 3442
 
6.9%
4 2539
 
5.1%
ValueCountFrequency (%)
187 3
< 0.1%
140 5
< 0.1%
139 1
 
< 0.1%
133 1
 
< 0.1%
124 2
 
< 0.1%

Food_12m
Real number (ℝ)

Distinct42
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.91748
Minimum0
Maximum114
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.319909image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum114
Range114
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.608962741
Coefficient of variation (CV)2.843618107
Kurtosis433.8072451
Mean0.91748
Median Absolute Deviation (MAD)0
Skewness13.85156464
Sum45874
Variance6.806686583
MonotonicityNot monotonic
2023-04-05T23:08:25.387130image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
5 723
 
1.4%
6 470
 
0.9%
7 316
 
0.6%
8 220
 
0.4%
9 194
 
0.4%
Other values (32) 618
 
1.2%
ValueCountFrequency (%)
0 34180
68.4%
1 6851
 
13.7%
2 3390
 
6.8%
3 1911
 
3.8%
4 1127
 
2.3%
ValueCountFrequency (%)
114 5
< 0.1%
80 1
 
< 0.1%
68 1
 
< 0.1%
56 2
 
< 0.1%
55 2
 
< 0.1%

Auto_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15662
Minimum0
Maximum57
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.445475image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum57
Range57
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.435385447
Coefficient of variation (CV)9.1647647
Kurtosis970.2156726
Mean0.15662
Median Absolute Deviation (MAD)0
Skewness28.46302955
Sum7831
Variance2.060331382
MonotonicityNot monotonic
2023-04-05T23:08:25.498012image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
5 36
 
0.1%
33 33
 
0.1%
6 25
 
0.1%
57 16
 
< 0.1%
12 12
 
< 0.1%
Other values (9) 42
 
0.1%
ValueCountFrequency (%)
0 46021
92.0%
1 2983
 
6.0%
2 620
 
1.2%
3 159
 
0.3%
4 53
 
0.1%
ValueCountFrequency (%)
57 16
< 0.1%
33 33
0.1%
17 4
 
< 0.1%
15 1
 
< 0.1%
14 2
 
< 0.1%

ClothStores_12m
Real number (ℝ)

Distinct41
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.89714
Minimum0
Maximum59
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.564756image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile8
Maximum59
Range59
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.372338547
Coefficient of variation (CV)1.777590766
Kurtosis34.01497166
Mean1.89714
Median Absolute Deviation (MAD)1
Skewness4.244303483
Sum94857
Variance11.37266727
MonotonicityNot monotonic
2023-04-05T23:08:25.629490image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
5 1730
 
3.5%
6 1223
 
2.4%
7 878
 
1.8%
8 622
 
1.2%
9 504
 
1.0%
Other values (31) 1742
 
3.5%
ValueCountFrequency (%)
0 24277
48.6%
1 8140
 
16.3%
2 5228
 
10.5%
3 3403
 
6.8%
4 2253
 
4.5%
ValueCountFrequency (%)
59 1
 
< 0.1%
57 9
< 0.1%
45 11
< 0.1%
42 1
 
< 0.1%
38 2
 
< 0.1%

MiscServices_12m
Real number (ℝ)

Distinct58
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90552
Minimum0
Maximum93
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.704074image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum93
Range93
Interquartile range (IQR)1

Descriptive statistics

Standard deviation3.282427306
Coefficient of variation (CV)3.624908677
Kurtosis177.2661933
Mean0.90552
Median Absolute Deviation (MAD)0
Skewness11.07163845
Sum45276
Variance10.77432902
MonotonicityNot monotonic
2023-04-05T23:08:25.774429image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
5 456
 
0.9%
6 334
 
0.7%
7 222
 
0.4%
8 139
 
0.3%
9 101
 
0.2%
Other values (48) 721
 
1.4%
ValueCountFrequency (%)
0 34785
69.6%
1 7825
 
15.7%
2 3072
 
6.1%
3 1541
 
3.1%
4 804
 
1.6%
ValueCountFrequency (%)
93 3
 
< 0.1%
78 1
 
< 0.1%
77 3
 
< 0.1%
66 10
< 0.1%
65 6
< 0.1%

HomeF_12m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07982
Minimum0
Maximum23
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:25.834859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum23
Range23
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4301307567
Coefficient of variation (CV)5.388759167
Kurtosis451.2791605
Mean0.07982
Median Absolute Deviation (MAD)0
Skewness13.94272501
Sum3991
Variance0.1850124678
MonotonicityNot monotonic
2023-04-05T23:08:25.885545image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
5 39
 
0.1%
7 6
 
< 0.1%
6 5
 
< 0.1%
8 3
 
< 0.1%
10 2
 
< 0.1%
Other values (3) 4
 
< 0.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1971
 
3.9%
2 488
 
1.0%
3 134
 
0.3%
4 63
 
0.1%
ValueCountFrequency (%)
23 1
 
< 0.1%
22 1
 
< 0.1%
17 2
< 0.1%
10 2
< 0.1%
8 3
< 0.1%

Electronics_12m
Real number (ℝ)

Distinct51
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.28572
Minimum0
Maximum133
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.031546image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum133
Range133
Interquartile range (IQR)1

Descriptive statistics

Standard deviation4.000290505
Coefficient of variation (CV)3.111323232
Kurtosis328.1721715
Mean1.28572
Median Absolute Deviation (MAD)0
Skewness13.51461061
Sum64286
Variance16.00232413
MonotonicityNot monotonic
2023-04-05T23:08:26.106698image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
5 826
 
1.7%
6 600
 
1.2%
7 412
 
0.8%
8 389
 
0.8%
9 274
 
0.5%
Other values (41) 1331
 
2.7%
ValueCountFrequency (%)
0 32112
64.2%
1 7727
 
15.5%
2 3378
 
6.8%
3 1892
 
3.8%
4 1059
 
2.1%
ValueCountFrequency (%)
133 9
< 0.1%
131 1
 
< 0.1%
87 2
 
< 0.1%
85 4
 
< 0.1%
82 13
< 0.1%

MusicStores_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct18
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.04938
Minimum0
Maximum163
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.170133image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum163
Range163
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.715948864
Coefficient of variation (CV)34.74987575
Kurtosis8177.573029
Mean0.04938
Median Absolute Deviation (MAD)0
Skewness87.28925641
Sum2469
Variance2.944480505
MonotonicityNot monotonic
2023-04-05T23:08:26.226067image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
5 25
 
0.1%
9 9
 
< 0.1%
6 9
 
< 0.1%
14 8
 
< 0.1%
24 6
 
< 0.1%
Other values (8) 18
 
< 0.1%
ValueCountFrequency (%)
0 49307
98.6%
1 417
 
0.8%
2 116
 
0.2%
3 54
 
0.1%
4 31
 
0.1%
ValueCountFrequency (%)
163 5
< 0.1%
65 1
 
< 0.1%
24 6
< 0.1%
17 2
 
< 0.1%
15 1
 
< 0.1%

Restaurants_12m
Real number (ℝ)

Distinct116
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9884
Minimum0
Maximum211
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.301027image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q35
95-th percentile22
Maximum211
Range211
Interquartile range (IQR)5

Descriptive statistics

Standard deviation10.36514226
Coefficient of variation (CV)2.077849063
Kurtosis43.35942087
Mean4.9884
Median Absolute Deviation (MAD)1
Skewness5.114187663
Sum249420
Variance107.4361742
MonotonicityNot monotonic
2023-04-05T23:08:26.373768image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
5 1787
 
3.6%
6 1459
 
2.9%
7 1278
 
2.6%
8 1090
 
2.2%
9 908
 
1.8%
Other values (106) 7539
 
15.1%
ValueCountFrequency (%)
0 20254
40.5%
1 6416
 
12.8%
2 4003
 
8.0%
3 3018
 
6.0%
4 2248
 
4.5%
ValueCountFrequency (%)
211 1
 
< 0.1%
201 1
 
< 0.1%
196 3
< 0.1%
161 1
 
< 0.1%
150 5
< 0.1%

DigitalGoods_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct53
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.56234
Minimum0
Maximum184
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.446659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum184
Range184
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.329892456
Coefficient of variation (CV)7.699776748
Kurtosis697.1504599
Mean0.56234
Median Absolute Deviation (MAD)0
Skewness22.67581288
Sum28117
Variance18.74796868
MonotonicityNot monotonic
2023-04-05T23:08:26.518247image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
5 213
 
0.4%
6 126
 
0.3%
7 119
 
0.2%
9 111
 
0.2%
10 69
 
0.1%
Other values (43) 517
 
1.0%
ValueCountFrequency (%)
0 44043
88.1%
1 2590
 
5.2%
2 933
 
1.9%
3 798
 
1.6%
4 481
 
1.0%
ValueCountFrequency (%)
184 5
< 0.1%
137 7
< 0.1%
128 8
< 0.1%
121 6
< 0.1%
80 6
< 0.1%

Alcohol_12m
Real number (ℝ)

Distinct44
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.40314
Minimum0
Maximum105
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.597333image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum105
Range105
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.003411693
Coefficient of variation (CV)4.969518513
Kurtosis661.1060958
Mean0.40314
Median Absolute Deviation (MAD)0
Skewness18.19384547
Sum20157
Variance4.013658414
MonotonicityNot monotonic
2023-04-05T23:08:26.669149image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
5 234
 
0.5%
6 183
 
0.4%
7 129
 
0.3%
8 102
 
0.2%
10 62
 
0.1%
Other values (34) 364
 
0.7%
ValueCountFrequency (%)
0 43436
86.9%
1 3068
 
6.1%
2 1356
 
2.7%
3 694
 
1.4%
4 372
 
0.7%
ValueCountFrequency (%)
105 3
< 0.1%
91 1
 
< 0.1%
78 1
 
< 0.1%
50 1
 
< 0.1%
47 2
< 0.1%

Books_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct19
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.15562
Minimum0
Maximum102
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.732155image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum102
Range102
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.165654147
Coefficient of variation (CV)7.490387785
Kurtosis4749.355926
Mean0.15562
Median Absolute Deviation (MAD)0
Skewness57.77552351
Sum7781
Variance1.358749591
MonotonicityNot monotonic
2023-04-05T23:08:26.790314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
5 46
 
0.1%
7 31
 
0.1%
6 23
 
< 0.1%
8 9
 
< 0.1%
24 6
 
< 0.1%
Other values (9) 27
 
0.1%
ValueCountFrequency (%)
0 45427
90.9%
1 3235
 
6.5%
2 808
 
1.6%
3 246
 
0.5%
4 142
 
0.3%
ValueCountFrequency (%)
102 4
< 0.1%
34 2
 
< 0.1%
27 6
< 0.1%
24 6
< 0.1%
15 4
< 0.1%

Jewelry_12m
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.18356
Minimum0
Maximum44
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.852329image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum44
Range44
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7054329728
Coefficient of variation (CV)3.84306479
Kurtosis636.7629954
Mean0.18356
Median Absolute Deviation (MAD)0
Skewness14.29820106
Sum9178
Variance0.4976356791
MonotonicityNot monotonic
2023-04-05T23:08:26.902803image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
5 74
 
0.1%
6 41
 
0.1%
7 12
 
< 0.1%
8 11
 
< 0.1%
9 9
 
< 0.1%
Other values (4) 17
 
< 0.1%
ValueCountFrequency (%)
0 44421
88.8%
1 3638
 
7.3%
2 1101
 
2.2%
3 491
 
1.0%
4 185
 
0.4%
ValueCountFrequency (%)
44 2
 
< 0.1%
14 4
< 0.1%
11 2
 
< 0.1%
10 9
< 0.1%
9 9
< 0.1%

DirectM_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07514
Minimum0
Maximum35
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:26.957982image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4828857463
Coefficient of variation (CV)6.42648052
Kurtosis920.1343764
Mean0.07514
Median Absolute Deviation (MAD)0
Skewness21.74502737
Sum3757
Variance0.233178644
MonotonicityNot monotonic
2023-04-05T23:08:27.012521image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
7 18
 
< 0.1%
5 15
 
< 0.1%
6 13
 
< 0.1%
12 10
 
< 0.1%
14 5
 
< 0.1%
Other values (4) 10
 
< 0.1%
ValueCountFrequency (%)
0 47389
94.8%
1 2118
 
4.2%
2 292
 
0.6%
3 88
 
0.2%
4 42
 
0.1%
ValueCountFrequency (%)
35 1
 
< 0.1%
19 4
 
< 0.1%
14 5
< 0.1%
12 10
< 0.1%
11 1
 
< 0.1%

Cash_12m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.072857image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:27.118124image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00088
Minimum0
Maximum5
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.165464image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.04426358306
Coefficient of variation (CV)50.2995262
Kurtosis7567.308021
Mean0.00088
Median Absolute Deviation (MAD)0
Skewness77.89338677
Sum44
Variance0.001959264785
MonotonicityNot monotonic
2023-04-05T23:08:27.216577image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
1 26
 
0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
5 2
 
< 0.1%
ValueCountFrequency (%)
5 2
 
< 0.1%
3 2
 
< 0.1%
2 1
 
< 0.1%
1 26
 
0.1%
0 49969
99.9%

FS_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00138
Minimum0
Maximum1
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.266197image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.03712308126
Coefficient of variation (CV)26.90078352
Kurtosis719.7111522
Mean0.00138
Median Absolute Deviation (MAD)0
Skewness26.86414644
Sum69
Variance0.001378123162
MonotonicityNot monotonic
2023-04-05T23:08:27.315870image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
0 49931
99.9%
1 69
 
0.1%
ValueCountFrequency (%)
1 69
 
0.1%
0 49931
99.9%

RentPayments_12m
Real number (ℝ)

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.62926
Minimum0
Maximum13
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.367340image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.428710144
Coefficient of variation (CV)2.27046077
Kurtosis8.04876218
Mean0.62926
Median Absolute Deviation (MAD)0
Skewness2.738019177
Sum31463
Variance2.041212677
MonotonicityNot monotonic
2023-04-05T23:08:27.512221image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
5 733
 
1.5%
6 428
 
0.9%
7 325
 
0.7%
8 130
 
0.3%
9 64
 
0.1%
Other values (3) 21
 
< 0.1%
ValueCountFrequency (%)
0 38583
77.2%
1 3266
 
6.5%
2 2806
 
5.6%
3 2330
 
4.7%
4 1314
 
2.6%
ValueCountFrequency (%)
13 1
 
< 0.1%
11 2
 
< 0.1%
10 18
 
< 0.1%
9 64
0.1%
8 130
0.3%

WalletLoad_12m
Real number (ℝ)

Distinct73
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9795
Minimum0
Maximum225
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.583374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum225
Range225
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.473615989
Coefficient of variation (CV)4.567244501
Kurtosis569.5985459
Mean0.9795
Median Absolute Deviation (MAD)0
Skewness17.61054299
Sum48975
Variance20.01324001
MonotonicityNot monotonic
2023-04-05T23:08:27.653174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
5 548
 
1.1%
6 411
 
0.8%
7 266
 
0.5%
9 223
 
0.4%
8 213
 
0.4%
Other values (63) 1105
 
2.2%
ValueCountFrequency (%)
0 39449
78.9%
1 3921
 
7.8%
2 1912
 
3.8%
3 1153
 
2.3%
4 799
 
1.6%
ValueCountFrequency (%)
225 2
< 0.1%
202 1
< 0.1%
184 1
< 0.1%
162 1
< 0.1%
144 2
< 0.1%

BusinessServ_12m
Real number (ℝ)

Distinct63
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.552
Minimum0
Maximum211
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.726480image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile6
Maximum211
Range211
Interquartile range (IQR)2

Descriptive statistics

Standard deviation5.539576675
Coefficient of variation (CV)3.569314868
Kurtosis404.4159115
Mean1.552
Median Absolute Deviation (MAD)0
Skewness16.30107829
Sum77600
Variance30.68690974
MonotonicityNot monotonic
2023-04-05T23:08:27.794277image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
5 986
 
2.0%
6 756
 
1.5%
7 505
 
1.0%
8 317
 
0.6%
9 225
 
0.4%
Other values (53) 1153
 
2.3%
ValueCountFrequency (%)
0 28973
57.9%
1 8419
 
16.8%
2 4421
 
8.8%
3 2568
 
5.1%
4 1677
 
3.4%
ValueCountFrequency (%)
211 5
 
< 0.1%
149 4
 
< 0.1%
130 14
< 0.1%
114 4
 
< 0.1%
107 7
< 0.1%

ProfServ_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.23736
Minimum0
Maximum42
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.860952image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.442366749
Coefficient of variation (CV)6.076705212
Kurtosis543.1740231
Mean0.23736
Median Absolute Deviation (MAD)0
Skewness20.80803992
Sum11868
Variance2.080421839
MonotonicityNot monotonic
2023-04-05T23:08:27.917348image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
5 91
 
0.2%
40 34
 
0.1%
9 27
 
0.1%
8 26
 
0.1%
6 26
 
0.1%
Other values (16) 90
 
0.2%
ValueCountFrequency (%)
0 44022
88.0%
1 3979
 
8.0%
2 1173
 
2.3%
3 391
 
0.8%
4 141
 
0.3%
ValueCountFrequency (%)
42 9
 
< 0.1%
40 34
0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
27 2
 
< 0.1%

Education_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct38
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.38266
Minimum0
Maximum95
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:27.981566image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum95
Range95
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.128558653
Coefficient of variation (CV)5.562532413
Kurtosis739.0244771
Mean0.38266
Median Absolute Deviation (MAD)0
Skewness22.97968228
Sum19133
Variance4.53076194
MonotonicityNot monotonic
2023-04-05T23:08:28.047387image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
5 176
 
0.4%
6 110
 
0.2%
7 48
 
0.1%
9 34
 
0.1%
8 28
 
0.1%
Other values (28) 168
 
0.3%
ValueCountFrequency (%)
0 41554
83.1%
1 5057
 
10.1%
2 1814
 
3.6%
3 660
 
1.3%
4 351
 
0.7%
ValueCountFrequency (%)
95 1
 
< 0.1%
83 12
< 0.1%
44 6
< 0.1%
43 5
< 0.1%
42 8
< 0.1%

GovtServices_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct59
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.33948
Minimum0
Maximum1127
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.117992image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum1127
Range1127
Interquartile range (IQR)1

Descriptive statistics

Standard deviation16.38762229
Coefficient of variation (CV)12.23431652
Kurtosis2880.094419
Mean1.33948
Median Absolute Deviation (MAD)0
Skewness47.9914472
Sum66974
Variance268.5541644
MonotonicityNot monotonic
2023-04-05T23:08:28.190135image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
5 547
 
1.1%
6 400
 
0.8%
7 319
 
0.6%
8 173
 
0.3%
9 139
 
0.3%
Other values (49) 808
 
1.6%
ValueCountFrequency (%)
0 36573
73.1%
1 5756
 
11.5%
2 2805
 
5.6%
3 1556
 
3.1%
4 924
 
1.8%
ValueCountFrequency (%)
1127 6
 
< 0.1%
390 33
0.1%
217 2
 
< 0.1%
171 1
 
< 0.1%
157 1
 
< 0.1%

Agri_amt_12m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.255828image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:28.302282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

Contract_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct235
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean220.2849898
Minimum0
Maximum440000
Zeros49536
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.371202image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum440000
Range440000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6200.959492
Coefficient of variation (CV)28.14971414
Kurtosis2493.646558
Mean220.2849898
Median Absolute Deviation (MAD)0
Skewness45.61014742
Sum11014249.49
Variance38451898.63
MonotonicityNot monotonic
2023-04-05T23:08:28.441930image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49536
99.1%
199 18
 
< 0.1%
1000 9
 
< 0.1%
1299 9
 
< 0.1%
100000 8
 
< 0.1%
2800 8
 
< 0.1%
10000 7
 
< 0.1%
50000 7
 
< 0.1%
68355 6
 
< 0.1%
30000 6
 
< 0.1%
Other values (225) 386
 
0.8%
ValueCountFrequency (%)
0 49536
99.1%
10 1
 
< 0.1%
25 1
 
< 0.1%
50 6
 
< 0.1%
71.58 1
 
< 0.1%
ValueCountFrequency (%)
440000 1
< 0.1%
405200 1
< 0.1%
400000 1
< 0.1%
395000 1
< 0.1%
380000 1
< 0.1%

Airline_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1492
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4669.319054
Minimum0
Maximum2694664
Zeros46359
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.512308image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3919.5
Maximum2694664
Range2694664
Interquartile range (IQR)0

Descriptive statistics

Standard deviation55460.76836
Coefficient of variation (CV)11.87769945
Kurtosis1166.967589
Mean4669.319054
Median Absolute Deviation (MAD)0
Skewness30.18308024
Sum233465952.7
Variance3075896827
MonotonicityNot monotonic
2023-04-05T23:08:28.592063image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46359
92.7%
150 72
 
0.1%
300 66
 
0.1%
250 60
 
0.1%
200 52
 
0.1%
100 44
 
0.1%
450 40
 
0.1%
170811 33
 
0.1%
400 31
 
0.1%
350 28
 
0.1%
Other values (1482) 3215
 
6.4%
ValueCountFrequency (%)
0 46359
92.7%
50 2
 
< 0.1%
99 3
 
< 0.1%
100 44
 
0.1%
104.25 2
 
< 0.1%
ValueCountFrequency (%)
2694664 2
 
< 0.1%
2444185.67 8
< 0.1%
2417315 1
 
< 0.1%
2088682 2
 
< 0.1%
1972827 2
 
< 0.1%

transport_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6259
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6478.121951
Minimum0
Maximum2169027.5
Zeros37570
Zeros (%)75.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.668533image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile24000
Maximum2169027.5
Range2169027.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47412.96853
Coefficient of variation (CV)7.318937323
Kurtosis561.0998448
Mean6478.121951
Median Absolute Deviation (MAD)0
Skewness20.68576257
Sum323906097.6
Variance2247989585
MonotonicityNot monotonic
2023-04-05T23:08:28.827490image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 37570
75.1%
2 221
 
0.4%
1000 117
 
0.2%
500 77
 
0.2%
1 65
 
0.1%
2000 53
 
0.1%
200 45
 
0.1%
1500 43
 
0.1%
300 34
 
0.1%
4 33
 
0.1%
Other values (6249) 11742
 
23.5%
ValueCountFrequency (%)
0 37570
75.1%
1 65
 
0.1%
1.3 1
 
< 0.1%
2 221
 
0.4%
2.8 1
 
< 0.1%
ValueCountFrequency (%)
2169027.5 1
 
< 0.1%
1403342.66 25
0.1%
1150000 6
 
< 0.1%
1027529.2 1
 
< 0.1%
1019060 1
 
< 0.1%

Insurance_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6348
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9789.220463
Minimum0
Maximum4484200
Zeros39445
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:28.902252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile42734.95
Maximum4484200
Range4484200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation70123.11161
Coefficient of variation (CV)7.163298843
Kurtosis1813.36226
Mean9789.220463
Median Absolute Deviation (MAD)0
Skewness34.35284618
Sum489461023.2
Variance4917250782
MonotonicityNot monotonic
2023-04-05T23:08:28.974060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39445
78.9%
1116060 33
 
0.1%
530 33
 
0.1%
10000 27
 
0.1%
15000 26
 
0.1%
5000 26
 
0.1%
3801 21
 
< 0.1%
102250 20
 
< 0.1%
887 20
 
< 0.1%
52250 18
 
< 0.1%
Other values (6338) 10331
 
20.7%
ValueCountFrequency (%)
0 39445
78.9%
1 1
 
< 0.1%
2 5
 
< 0.1%
11 1
 
< 0.1%
26 1
 
< 0.1%
ValueCountFrequency (%)
4484200 1
 
< 0.1%
4275963 5
< 0.1%
2176772.64 2
 
< 0.1%
1486353.22 1
 
< 0.1%
1329325.26 4
< 0.1%

Hotels_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct6237
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6508.666604
Minimum0
Maximum4479268.69
Zeros36891
Zeros (%)73.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.053273image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3356
95-th percentile25603.06
Maximum4479268.69
Range4479268.69
Interquartile range (IQR)356

Descriptive statistics

Standard deviation49810.4365
Coefficient of variation (CV)7.65294023
Kurtosis3040.056778
Mean6508.666604
Median Absolute Deviation (MAD)0
Skewness42.77689715
Sum325433330.2
Variance2481079584
MonotonicityNot monotonic
2023-04-05T23:08:29.126038image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36891
73.8%
3000 48
 
0.1%
2000 43
 
0.1%
1760 34
 
0.1%
1500 30
 
0.1%
5000 29
 
0.1%
10000 29
 
0.1%
1000 26
 
0.1%
4000 26
 
0.1%
2500 25
 
0.1%
Other values (6227) 12819
 
25.6%
ValueCountFrequency (%)
0 36891
73.8%
1 4
 
< 0.1%
2 18
 
< 0.1%
6 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
4479268.69 2
 
< 0.1%
2260639.29 2
 
< 0.1%
1723207.74 7
< 0.1%
1576184.34 2
 
< 0.1%
1027180.5 4
< 0.1%

Railways_amt_12m
Real number (ℝ)

Distinct6459
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5483.707647
Minimum0
Maximum1080511
Zeros39278
Zeros (%)78.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.201518image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile22424.38
Maximum1080511
Range1080511
Interquartile range (IQR)0

Descriptive statistics

Standard deviation32094.90815
Coefficient of variation (CV)5.852775206
Kurtosis295.10659
Mean5483.707647
Median Absolute Deviation (MAD)0
Skewness14.74147247
Sum274185382.4
Variance1030083129
MonotonicityNot monotonic
2023-04-05T23:08:29.279325image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39278
78.6%
500 45
 
0.1%
3897 33
 
0.1%
200 30
 
0.1%
300 29
 
0.1%
102.12 27
 
0.1%
57457.7 25
 
0.1%
100 24
 
< 0.1%
644062.26 20
 
< 0.1%
1 18
 
< 0.1%
Other values (6449) 10471
 
20.9%
ValueCountFrequency (%)
0 39278
78.6%
1 18
 
< 0.1%
1.21 1
 
< 0.1%
1.53 1
 
< 0.1%
2 4
 
< 0.1%
ValueCountFrequency (%)
1080511 2
 
< 0.1%
820633.41 11
< 0.1%
785491 2
 
< 0.1%
783356.6 1
 
< 0.1%
650000 2
 
< 0.1%

Airports_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.370073
Minimum0
Maximum14471.55
Zeros49945
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.348677image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum14471.55
Range14471.55
Interquartile range (IQR)0

Descriptive statistics

Standard deviation190.1376108
Coefficient of variation (CV)43.50902394
Kurtosis2906.5728
Mean4.370073
Median Absolute Deviation (MAD)0
Skewness52.14727746
Sum218503.65
Variance36152.31103
MonotonicityNot monotonic
2023-04-05T23:08:29.407744image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 49945
99.9%
10300 12
 
< 0.1%
750 5
 
< 0.1%
150 3
 
< 0.1%
600 3
 
< 0.1%
1500 3
 
< 0.1%
5200 3
 
< 0.1%
500 2
 
< 0.1%
2175.53 2
 
< 0.1%
1920 2
 
< 0.1%
Other values (17) 20
 
< 0.1%
ValueCountFrequency (%)
0 49945
99.9%
121.09 1
 
< 0.1%
130 1
 
< 0.1%
150 3
 
< 0.1%
240 1
 
< 0.1%
ValueCountFrequency (%)
14471.55 1
 
< 0.1%
10300 12
< 0.1%
8732.42 1
 
< 0.1%
6195 1
 
< 0.1%
5200 3
 
< 0.1%

Utility_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14777
Distinct (%)29.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20979.84211
Minimum0
Maximum4087763.19
Zeros20688
Zeros (%)41.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.485643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median984.6
Q37823.165
95-th percentile67000
Maximum4087763.19
Range4087763.19
Interquartile range (IQR)7823.165

Descriptive statistics

Standard deviation141481.9163
Coefficient of variation (CV)6.743707393
Kurtosis547.0708129
Mean20979.84211
Median Absolute Deviation (MAD)984.6
Skewness21.14555362
Sum1048992105
Variance2.001713264 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:29.562097image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20688
41.4%
2 204
 
0.4%
1947 149
 
0.3%
1178.82 139
 
0.3%
666 132
 
0.3%
2999 110
 
0.2%
597 94
 
0.2%
4000 84
 
0.2%
719 80
 
0.2%
1298 67
 
0.1%
Other values (14767) 28253
56.5%
ValueCountFrequency (%)
0 20688
41.4%
1 10
 
< 0.1%
1.18 1
 
< 0.1%
1.5 1
 
< 0.1%
2 204
 
0.4%
ValueCountFrequency (%)
4087763.19 34
0.1%
3293669.12 3
 
< 0.1%
2983747.64 14
< 0.1%
2179970.74 2
 
< 0.1%
2135000 2
 
< 0.1%

Retail_amt_12m
Real number (ℝ)

Distinct11163
Distinct (%)22.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10277.3661
Minimum0
Maximum2444657.25
Zeros25725
Zeros (%)51.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.644980image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34815.2775
95-th percentile40845.3
Maximum2444657.25
Range2444657.25
Interquartile range (IQR)4815.2775

Descriptive statistics

Standard deviation49404.26127
Coefficient of variation (CV)4.807093645
Kurtosis477.3922902
Mean10277.3661
Median Absolute Deviation (MAD)0
Skewness17.10848078
Sum513868305.1
Variance2440781032
MonotonicityNot monotonic
2023-04-05T23:08:29.721926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25725
51.4%
4000 155
 
0.3%
5000 88
 
0.2%
1000 88
 
0.2%
500 83
 
0.2%
2000 75
 
0.1%
10000 71
 
0.1%
300 56
 
0.1%
3000 55
 
0.1%
2500 48
 
0.1%
Other values (11153) 23556
47.1%
ValueCountFrequency (%)
0 25725
51.4%
1 10
 
< 0.1%
2 47
 
0.1%
3 1
 
< 0.1%
4.5 1
 
< 0.1%
ValueCountFrequency (%)
2444657.25 1
 
< 0.1%
2028399.4 1
 
< 0.1%
1950777.21 1
 
< 0.1%
1700000 1
 
< 0.1%
1447823 11
< 0.1%

Medical_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct8057
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5956.067773
Minimum0
Maximum2402098
Zeros32314
Zeros (%)64.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:29.796643image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31402
95-th percentile23824.6725
Maximum2402098
Range2402098
Interquartile range (IQR)1402

Descriptive statistics

Standard deviation37995.19547
Coefficient of variation (CV)6.379241626
Kurtosis1358.903652
Mean5956.067773
Median Absolute Deviation (MAD)0
Skewness28.47865804
Sum297803388.7
Variance1443634878
MonotonicityNot monotonic
2023-04-05T23:08:29.959878image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1000 88
 
0.2%
800 78
 
0.2%
600 76
 
0.2%
500 73
 
0.1%
400 66
 
0.1%
10000 62
 
0.1%
1500 60
 
0.1%
386 58
 
0.1%
Other values (8047) 16998
34.0%
ValueCountFrequency (%)
0 32314
64.6%
1 127
 
0.3%
1.74 1
 
< 0.1%
2 16
 
< 0.1%
2.09 1
 
< 0.1%
ValueCountFrequency (%)
2402098 3
< 0.1%
1920000 2
< 0.1%
1200021 1
 
< 0.1%
1004101.15 2
< 0.1%
991851 3
< 0.1%

Fuel_amt_12m
Real number (ℝ)

Distinct15280
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7818.260737
Minimum0
Maximum720806.32
Zeros21967
Zeros (%)43.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.033558image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median957.51
Q38259.5975
95-th percentile34593.08
Maximum720806.32
Range720806.32
Interquartile range (IQR)8259.5975

Descriptive statistics

Standard deviation19450.44167
Coefficient of variation (CV)2.487822078
Kurtosis207.5981641
Mean7818.260737
Median Absolute Deviation (MAD)957.51
Skewness9.776964854
Sum390913036.8
Variance378319681.1
MonotonicityNot monotonic
2023-04-05T23:08:30.110031image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21967
43.9%
2023.6 248
 
0.5%
3035.4 237
 
0.5%
2020 208
 
0.4%
1011.8 201
 
0.4%
1010 182
 
0.4%
505 153
 
0.3%
4047.2 128
 
0.3%
2529.5 100
 
0.2%
505.9 97
 
0.2%
Other values (15270) 26479
53.0%
ValueCountFrequency (%)
0 21967
43.9%
40.47 1
 
< 0.1%
41.36 2
 
< 0.1%
50.5 1
 
< 0.1%
70.7 1
 
< 0.1%
ValueCountFrequency (%)
720806.32 3
< 0.1%
642096.54 2
< 0.1%
457796.21 2
< 0.1%
301441.79 3
< 0.1%
280881.76 3
< 0.1%

DeptStores_amt_12m
Real number (ℝ)

Distinct16736
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11766.24459
Minimum0
Maximum2500871.5
Zeros20359
Zeros (%)40.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.186850image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1025.85
Q36647.36
95-th percentile30875.1925
Maximum2500871.5
Range2500871.5
Interquartile range (IQR)6647.36

Descriptive statistics

Standard deviation64171.46191
Coefficient of variation (CV)5.453860949
Kurtosis434.6925681
Mean11766.24459
Median Absolute Deviation (MAD)1025.85
Skewness17.05207472
Sum588312229.7
Variance4117976523
MonotonicityNot monotonic
2023-04-05T23:08:30.269480image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20359
40.7%
1000 50
 
0.1%
10000 43
 
0.1%
3889.84 34
 
0.1%
900 33
 
0.1%
17463.93 33
 
0.1%
200 31
 
0.1%
25000 29
 
0.1%
3000 27
 
0.1%
5000 27
 
0.1%
Other values (16726) 29334
58.7%
ValueCountFrequency (%)
0 20359
40.7%
1 6
 
< 0.1%
1.36 1
 
< 0.1%
2 1
 
< 0.1%
2.34 2
 
< 0.1%
ValueCountFrequency (%)
2500871.5 3
 
< 0.1%
2428372 1
 
< 0.1%
2059552.18 8
< 0.1%
1392592.48 4
< 0.1%
1307000 2
 
< 0.1%

Food_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5214
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1385.462862
Minimum0
Maximum1096500
Zeros34180
Zeros (%)68.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.351482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3485
95-th percentile5079.79
Maximum1096500
Range1096500
Interquartile range (IQR)485

Descriptive statistics

Standard deviation14397.16652
Coefficient of variation (CV)10.39159325
Kurtosis3266.876924
Mean1385.462862
Median Absolute Deviation (MAD)0
Skewness49.93555124
Sum69273143.11
Variance207278403.8
MonotonicityNot monotonic
2023-04-05T23:08:30.429052image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34180
68.4%
2 92
 
0.2%
500 73
 
0.1%
400 57
 
0.1%
1000 50
 
0.1%
450 49
 
0.1%
200 47
 
0.1%
300 46
 
0.1%
480 46
 
0.1%
4 43
 
0.1%
Other values (5204) 15317
30.6%
ValueCountFrequency (%)
0 34180
68.4%
1 3
 
< 0.1%
2 92
 
0.2%
3.12 1
 
< 0.1%
4 43
 
0.1%
ValueCountFrequency (%)
1096500 2
 
< 0.1%
1046805 3
< 0.1%
539123 1
 
< 0.1%
521890 1
 
< 0.1%
488020 5
< 0.1%

Auto_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1867
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2167.957446
Minimum0
Maximum1219987
Zeros46021
Zeros (%)92.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.507980image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4747.1
Maximum1219987
Range1219987
Interquartile range (IQR)0

Descriptive statistics

Standard deviation26685.79818
Coefficient of variation (CV)12.30918911
Kurtosis777.9184609
Mean2167.957446
Median Absolute Deviation (MAD)0
Skewness25.52549873
Sum108397872.3
Variance712131824.5
MonotonicityNot monotonic
2023-04-05T23:08:30.591330image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46021
92.0%
10000 56
 
0.1%
670267.04 33
 
0.1%
25000 29
 
0.1%
11000 27
 
0.1%
3000 25
 
0.1%
5000 24
 
< 0.1%
1000 23
 
< 0.1%
2000 21
 
< 0.1%
21000 21
 
< 0.1%
Other values (1857) 3720
 
7.4%
ValueCountFrequency (%)
0 46021
92.0%
59 2
 
< 0.1%
60 2
 
< 0.1%
66 1
 
< 0.1%
84 1
 
< 0.1%
ValueCountFrequency (%)
1219987 4
 
< 0.1%
802400 1
 
< 0.1%
800000 4
 
< 0.1%
709100 4
 
< 0.1%
670267.04 33
0.1%

ClothStores_amt_12m
Real number (ℝ)

Distinct12156
Distinct (%)24.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9433.808793
Minimum0
Maximum1154700
Zeros24277
Zeros (%)48.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.670374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median499
Q37897.24
95-th percentile39944.9
Maximum1154700
Range1154700
Interquartile range (IQR)7897.24

Descriptive statistics

Standard deviation31098.84787
Coefficient of variation (CV)3.296531502
Kurtosis291.5345429
Mean9433.808793
Median Absolute Deviation (MAD)499
Skewness13.04381894
Sum471690439.6
Variance967138338.6
MonotonicityNot monotonic
2023-04-05T23:08:30.748273image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24277
48.6%
5000 54
 
0.1%
3000 52
 
0.1%
1000 49
 
0.1%
400 48
 
0.1%
2000 43
 
0.1%
1500 42
 
0.1%
1499 36
 
0.1%
599 34
 
0.1%
999 34
 
0.1%
Other values (12146) 25331
50.7%
ValueCountFrequency (%)
0 24277
48.6%
2 27
 
0.1%
3.1 1
 
< 0.1%
10 7
 
< 0.1%
11 2
 
< 0.1%
ValueCountFrequency (%)
1154700 3
< 0.1%
964208.44 3
< 0.1%
837031.06 4
< 0.1%
800000 1
 
< 0.1%
789448.5 1
 
< 0.1%

MiscServices_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct5445
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2870.836041
Minimum0
Maximum1568000
Zeros34785
Zeros (%)69.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:30.826198image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3308
95-th percentile11139.15
Maximum1568000
Range1568000
Interquartile range (IQR)308

Descriptive statistics

Standard deviation21446.42166
Coefficient of variation (CV)7.470444621
Kurtosis1377.045698
Mean2870.836041
Median Absolute Deviation (MAD)0
Skewness30.16463497
Sum143541802.1
Variance459949002.1
MonotonicityNot monotonic
2023-04-05T23:08:30.904459image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34785
69.6%
2 1374
 
2.7%
1000 73
 
0.1%
500 68
 
0.1%
600 64
 
0.1%
2000 60
 
0.1%
5000 56
 
0.1%
2500 53
 
0.1%
3000 52
 
0.1%
6000 51
 
0.1%
Other values (5435) 13364
 
26.7%
ValueCountFrequency (%)
0 34785
69.6%
1 10
 
< 0.1%
2 1374
 
2.7%
3 1
 
< 0.1%
4 11
 
< 0.1%
ValueCountFrequency (%)
1568000 1
< 0.1%
1105500 2
< 0.1%
1000705.7 2
< 0.1%
833000 2
< 0.1%
810929 2
< 0.1%

HomeF_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1244
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1107.691418
Minimum0
Maximum521180.38
Zeros47285
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.068040image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile800
Maximum521180.38
Range521180.38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11198.17701
Coefficient of variation (CV)10.10947348
Kurtosis961.430417
Mean1107.691418
Median Absolute Deviation (MAD)0
Skewness26.28062187
Sum55384570.89
Variance125399168.3
MonotonicityNot monotonic
2023-04-05T23:08:31.146892image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47285
94.6%
5000 32
 
0.1%
20000 25
 
0.1%
10000 21
 
< 0.1%
1000 16
 
< 0.1%
15000 13
 
< 0.1%
4200 13
 
< 0.1%
4449 12
 
< 0.1%
8000 12
 
< 0.1%
30000 12
 
< 0.1%
Other values (1234) 2559
 
5.1%
ValueCountFrequency (%)
0 47285
94.6%
1 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
90 1
 
< 0.1%
ValueCountFrequency (%)
521180.38 2
 
< 0.1%
516155 1
 
< 0.1%
500000 6
< 0.1%
387326 1
 
< 0.1%
353000 1
 
< 0.1%

Electronics_amt_12m
Real number (ℝ)

Distinct8450
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7785.50485
Minimum0
Maximum1075000
Zeros32112
Zeros (%)64.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.223020image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32105
95-th percentile36104.53
Maximum1075000
Range1075000
Interquartile range (IQR)2105

Descriptive statistics

Standard deviation37669.26346
Coefficient of variation (CV)4.838384175
Kurtosis260.1614027
Mean7785.50485
Median Absolute Deviation (MAD)0
Skewness13.72312102
Sum389275242.5
Variance1418973409
MonotonicityNot monotonic
2023-04-05T23:08:31.300288image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 32112
64.2%
199 103
 
0.2%
1499 57
 
0.1%
549 52
 
0.1%
299 50
 
0.1%
2 42
 
0.1%
10000 41
 
0.1%
2000 41
 
0.1%
2999 40
 
0.1%
15000 36
 
0.1%
Other values (8440) 17426
34.9%
ValueCountFrequency (%)
0 32112
64.2%
1 25
 
0.1%
2 42
 
0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
1075000 1
 
< 0.1%
1004027.56 3
 
< 0.1%
959690 3
 
< 0.1%
942423 13
< 0.1%
790833.6 3
 
< 0.1%

MusicStores_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct246
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.767819
Minimum0
Maximum272142
Zeros49307
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.376893image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum272142
Range272142
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2954.615352
Coefficient of variation (CV)33.66399422
Kurtosis7219.326039
Mean87.767819
Median Absolute Deviation (MAD)0
Skewness80.00078775
Sum4388390.95
Variance8729751.876
MonotonicityNot monotonic
2023-04-05T23:08:31.455137image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 49307
98.6%
99 22
 
< 0.1%
2000 18
 
< 0.1%
149 14
 
< 0.1%
5000 14
 
< 0.1%
75 13
 
< 0.1%
1499 13
 
< 0.1%
449 13
 
< 0.1%
269 12
 
< 0.1%
169 11
 
< 0.1%
Other values (236) 563
 
1.1%
ValueCountFrequency (%)
0 49307
98.6%
5 3
 
< 0.1%
7 1
 
< 0.1%
15 5
 
< 0.1%
18 4
 
< 0.1%
ValueCountFrequency (%)
272142 5
< 0.1%
88411 1
 
< 0.1%
50179 2
 
< 0.1%
49500 2
 
< 0.1%
39000 1
 
< 0.1%

Restaurants_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct14564
Distinct (%)29.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5916.247728
Minimum0
Maximum1020000
Zeros20254
Zeros (%)40.5%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.536263image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median680.1
Q34861
95-th percentile24971
Maximum1020000
Range1020000
Interquartile range (IQR)4861

Descriptive statistics

Standard deviation22675.5409
Coefficient of variation (CV)3.832757169
Kurtosis668.8097281
Mean5916.247728
Median Absolute Deviation (MAD)680.1
Skewness20.79086653
Sum295812386.4
Variance514180154.9
MonotonicityNot monotonic
2023-04-05T23:08:31.617339image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 20254
40.5%
2 399
 
0.8%
4 152
 
0.3%
300 42
 
0.1%
6 37
 
0.1%
2061.65 33
 
0.1%
220 32
 
0.1%
1000 32
 
0.1%
900 31
 
0.1%
400 30
 
0.1%
Other values (14554) 28958
57.9%
ValueCountFrequency (%)
0 20254
40.5%
1 4
 
< 0.1%
2 399
 
0.8%
4 152
 
0.3%
6 37
 
0.1%
ValueCountFrequency (%)
1020000 1
 
< 0.1%
1000000 1
 
< 0.1%
863465.05 9
< 0.1%
657847.38 7
< 0.1%
495000 1
 
< 0.1%

DigitalGoods_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1822
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2473.969376
Minimum0
Maximum948600
Zeros44043
Zeros (%)88.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.692754image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1891
Maximum948600
Range948600
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30509.16017
Coefficient of variation (CV)12.33206865
Kurtosis531.4836965
Mean2473.969376
Median Absolute Deviation (MAD)0
Skewness21.24664222
Sum123698468.8
Variance930808854.4
MonotonicityNot monotonic
2023-04-05T23:08:31.764245image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44043
88.1%
2 169
 
0.3%
1300 120
 
0.2%
390 112
 
0.2%
299 106
 
0.2%
200 84
 
0.2%
387 71
 
0.1%
20 64
 
0.1%
567 64
 
0.1%
258 55
 
0.1%
Other values (1812) 5112
 
10.2%
ValueCountFrequency (%)
0 44043
88.1%
1 42
 
0.1%
2 169
 
0.3%
4 14
 
< 0.1%
5 3
 
< 0.1%
ValueCountFrequency (%)
948600 8
 
< 0.1%
884000 2
 
< 0.1%
865000 20
< 0.1%
811681.72 2
 
< 0.1%
602499 5
 
< 0.1%

Alcohol_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2019
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean797.6000446
Minimum0
Maximum399994
Zeros43436
Zeros (%)86.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.842566image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3683
Maximum399994
Range399994
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6130.755373
Coefficient of variation (CV)7.686503297
Kurtosis1671.293833
Mean797.6000446
Median Absolute Deviation (MAD)0
Skewness32.97707862
Sum39880002.23
Variance37586161.44
MonotonicityNot monotonic
2023-04-05T23:08:31.921003image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 43436
86.9%
900 48
 
0.1%
600 47
 
0.1%
360 42
 
0.1%
1200 34
 
0.1%
400 34
 
0.1%
800 31
 
0.1%
720 30
 
0.1%
300 30
 
0.1%
540 30
 
0.1%
Other values (2009) 6238
 
12.5%
ValueCountFrequency (%)
0 43436
86.9%
60 1
 
< 0.1%
90 4
 
< 0.1%
104 1
 
< 0.1%
105 2
 
< 0.1%
ValueCountFrequency (%)
399994 2
< 0.1%
390730 1
 
< 0.1%
390635 1
 
< 0.1%
231400 2
< 0.1%
200240 3
< 0.1%

Books_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct1938
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634.0098318
Minimum0
Maximum949000
Zeros45427
Zeros (%)90.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:31.999666image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1526
Maximum949000
Range949000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10100.5045
Coefficient of variation (CV)15.93114805
Kurtosis3809.320487
Mean634.0098318
Median Absolute Deviation (MAD)0
Skewness52.38559939
Sum31700491.59
Variance102020191.1
MonotonicityNot monotonic
2023-04-05T23:08:32.075513image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45427
90.9%
450 25
 
0.1%
400 22
 
< 0.1%
300 22
 
< 0.1%
40000 20
 
< 0.1%
900 19
 
< 0.1%
1000 18
 
< 0.1%
2500 18
 
< 0.1%
600 17
 
< 0.1%
1700 17
 
< 0.1%
Other values (1928) 4395
 
8.8%
ValueCountFrequency (%)
0 45427
90.9%
1 3
 
< 0.1%
1.51 1
 
< 0.1%
8 2
 
< 0.1%
10 5
 
< 0.1%
ValueCountFrequency (%)
949000 2
 
< 0.1%
464107.59 4
< 0.1%
400000 1
 
< 0.1%
368130 6
< 0.1%
281550 1
 
< 0.1%

Jewelry_amt_12m
Real number (ℝ)

Distinct2303
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5020.164728
Minimum0
Maximum1312235
Zeros44421
Zeros (%)88.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.237100image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20387.2
Maximum1312235
Range1312235
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31291.24714
Coefficient of variation (CV)6.233111628
Kurtosis274.1977494
Mean5020.164728
Median Absolute Deviation (MAD)0
Skewness13.52489059
Sum251008236.4
Variance979142147.6
MonotonicityNot monotonic
2023-04-05T23:08:32.316194image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44421
88.8%
10000 105
 
0.2%
5000 78
 
0.2%
20000 76
 
0.2%
30000 53
 
0.1%
6000 51
 
0.1%
2000 51
 
0.1%
4000 45
 
0.1%
15000 41
 
0.1%
50000 38
 
0.1%
Other values (2293) 5041
 
10.1%
ValueCountFrequency (%)
0 44421
88.8%
10 2
 
< 0.1%
110 1
 
< 0.1%
119 3
 
< 0.1%
120 1
 
< 0.1%
ValueCountFrequency (%)
1312235 1
< 0.1%
1126230 1
< 0.1%
832650 2
< 0.1%
829200 2
< 0.1%
724000 1
< 0.1%

DirectM_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct836
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean440.4139112
Minimum0
Maximum1839140.65
Zeros47389
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.400880image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile149
Maximum1839140.65
Range1839140.65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16126.08507
Coefficient of variation (CV)36.61574865
Kurtosis10640.73601
Mean440.4139112
Median Absolute Deviation (MAD)0
Skewness97.61371505
Sum22020695.56
Variance260050619.8
MonotonicityNot monotonic
2023-04-05T23:08:32.476881image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 47389
94.8%
199 390
 
0.8%
649 338
 
0.7%
499 169
 
0.3%
149 115
 
0.2%
398 29
 
0.1%
2 26
 
0.1%
1298 19
 
< 0.1%
998 15
 
< 0.1%
501 11
 
< 0.1%
Other values (826) 1499
 
3.0%
ValueCountFrequency (%)
0 47389
94.8%
1 1
 
< 0.1%
2 26
 
0.1%
12 2
 
< 0.1%
19 1
 
< 0.1%
ValueCountFrequency (%)
1839140.65 3
< 0.1%
1115580.42 1
 
< 0.1%
516502.12 1
 
< 0.1%
351866.94 1
 
< 0.1%
330896.88 1
 
< 0.1%

Cash_amt_12m
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.540141image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:32.587919image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

QuasiCash_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct17
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.913654
Minimum0
Maximum149644.47
Zeros49969
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.644847image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum149644.47
Range149644.47
Interquartile range (IQR)0

Descriptive statistics

Standard deviation967.3857349
Coefficient of variation (CV)108.5285266
Kurtosis22921.57892
Mean8.913654
Median Absolute Deviation (MAD)0
Skewness148.9790539
Sum445682.7
Variance935835.1601
MonotonicityNot monotonic
2023-04-05T23:08:32.701934image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
3393.16 4
 
< 0.1%
4457.23 4
 
< 0.1%
5007.12 3
 
< 0.1%
319.01 2
 
< 0.1%
149644.47 2
 
< 0.1%
21072.71 2
 
< 0.1%
2399.01 1
 
< 0.1%
8469.32 1
 
< 0.1%
Other values (7) 7
 
< 0.1%
ValueCountFrequency (%)
0 49969
99.9%
285.61 5
 
< 0.1%
319.01 2
 
< 0.1%
754.41 1
 
< 0.1%
2009.57 1
 
< 0.1%
ValueCountFrequency (%)
149644.47 2
< 0.1%
27988.24 1
< 0.1%
21072.71 2
< 0.1%
8469.32 1
< 0.1%
5013.32 1
< 0.1%

FS_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.366
Minimum0
Maximum30000
Zeros49931
Zeros (%)99.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.757174image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum30000
Range30000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation174.5065703
Coefficient of variation (CV)127.7500515
Kurtosis25755.09187
Mean1.366
Median Absolute Deviation (MAD)0
Skewness159.7054686
Sum68300
Variance30452.54309
MonotonicityNot monotonic
2023-04-05T23:08:32.803465image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=4)
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
30000 1
 
< 0.1%
24900 1
 
< 0.1%
ValueCountFrequency (%)
0 49931
99.9%
200 67
 
0.1%
24900 1
 
< 0.1%
30000 1
 
< 0.1%
ValueCountFrequency (%)
30000 1
 
< 0.1%
24900 1
 
< 0.1%
200 67
 
0.1%
0 49931
99.9%

RentPayments_amt_12m
Real number (ℝ)

Distinct6705
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17250.93866
Minimum0
Maximum1013828
Zeros38583
Zeros (%)77.2%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:32.873965image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile106470.675
Maximum1013828
Range1013828
Interquartile range (IQR)0

Descriptive statistics

Standard deviation51878.21575
Coefficient of variation (CV)3.007269156
Kurtosis42.62888392
Mean17250.93866
Median Absolute Deviation (MAD)0
Skewness5.359033025
Sum862546933
Variance2691349269
MonotonicityNot monotonic
2023-04-05T23:08:32.951812image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38583
77.2%
20300 65
 
0.1%
10150 58
 
0.1%
3540 57
 
0.1%
25375 42
 
0.1%
20200 40
 
0.1%
40600 30
 
0.1%
30420 28
 
0.1%
20310 27
 
0.1%
30300 25
 
0.1%
Other values (6695) 11045
 
22.1%
ValueCountFrequency (%)
0 38583
77.2%
1 1
 
< 0.1%
1.01 1
 
< 0.1%
2 18
 
< 0.1%
5.11 1
 
< 0.1%
ValueCountFrequency (%)
1013828 1
< 0.1%
959020 1
< 0.1%
891620.5 1
< 0.1%
807058 1
< 0.1%
797900 2
< 0.1%

WalletLoad_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct4467
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3405.023854
Minimum0
Maximum1835364.3
Zeros39449
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.027735image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile20336.72
Maximum1835364.3
Range1835364.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation20662.81433
Coefficient of variation (CV)6.06833174
Kurtosis2728.405834
Mean3405.023854
Median Absolute Deviation (MAD)0
Skewness38.26647813
Sum170251192.7
Variance426951896
MonotonicityNot monotonic
2023-04-05T23:08:33.102076image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 39449
78.9%
1023 139
 
0.3%
1000 123
 
0.2%
500 105
 
0.2%
2000 103
 
0.2%
4000 103
 
0.2%
10230 99
 
0.2%
2046 85
 
0.2%
5115 81
 
0.2%
20460 79
 
0.2%
Other values (4457) 9634
 
19.3%
ValueCountFrequency (%)
0 39449
78.9%
1 5
 
< 0.1%
1.02 5
 
< 0.1%
1.03 1
 
< 0.1%
2 43
 
0.1%
ValueCountFrequency (%)
1835364.3 2
 
< 0.1%
684317.7 4
< 0.1%
656226.57 6
< 0.1%
337932 7
< 0.1%
323330 2
 
< 0.1%

BusinessServ_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct10073
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10236.93259
Minimum0
Maximum4905650
Zeros28973
Zeros (%)57.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.189441image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31399
95-th percentile20072
Maximum4905650
Range4905650
Interquartile range (IQR)1399

Descriptive statistics

Standard deviation110315.3813
Coefficient of variation (CV)10.77621449
Kurtosis1051.347246
Mean10236.93259
Median Absolute Deviation (MAD)0
Skewness28.70445734
Sum511846629.6
Variance1.216948335 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:33.268682image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 28973
57.9%
1000 94
 
0.2%
600 65
 
0.1%
899 63
 
0.1%
1500 63
 
0.1%
1499 60
 
0.1%
500 56
 
0.1%
2 49
 
0.1%
400 48
 
0.1%
3000 45
 
0.1%
Other values (10063) 20484
41.0%
ValueCountFrequency (%)
0 28973
57.9%
1 17
 
< 0.1%
2 49
 
0.1%
3 1
 
< 0.1%
4 9
 
< 0.1%
ValueCountFrequency (%)
4905650 11
< 0.1%
3121264.01 1
 
< 0.1%
2828574 14
< 0.1%
2697100 4
 
< 0.1%
1894211.09 12
< 0.1%

ProfServ_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct2179
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2725.70208
Minimum0
Maximum1500000
Zeros44022
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.347515image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6807.2
Maximum1500000
Range1500000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation27657.61293
Coefficient of variation (CV)10.14696842
Kurtosis1000.913767
Mean2725.70208
Median Absolute Deviation (MAD)0
Skewness26.89576097
Sum136285104
Variance764943553.1
MonotonicityNot monotonic
2023-04-05T23:08:33.425769image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44022
88.0%
500 95
 
0.2%
1000 76
 
0.2%
1500 68
 
0.1%
3000 66
 
0.1%
5000 65
 
0.1%
10000 61
 
0.1%
4032 52
 
0.1%
2000 50
 
0.1%
400 40
 
0.1%
Other values (2169) 5405
 
10.8%
ValueCountFrequency (%)
0 44022
88.0%
1 8
 
< 0.1%
10 3
 
< 0.1%
29 2
 
< 0.1%
31 1
 
< 0.1%
ValueCountFrequency (%)
1500000 2
< 0.1%
1302900 2
< 0.1%
1300000 1
< 0.1%
1150000 1
< 0.1%
1125000 1
< 0.1%

Education_amt_12m
Real number (ℝ)

Distinct3859
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6434.501254
Minimum0
Maximum1505584
Zeros41554
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.600957image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile34443.63
Maximum1505584
Range1505584
Interquartile range (IQR)0

Descriptive statistics

Standard deviation37406.22845
Coefficient of variation (CV)5.813384281
Kurtosis451.9611095
Mean6434.501254
Median Absolute Deviation (MAD)0
Skewness17.12044735
Sum321725062.7
Variance1399225926
MonotonicityNot monotonic
2023-04-05T23:08:33.674009image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41554
83.1%
2 572
 
1.1%
455 41
 
0.1%
1000 40
 
0.1%
10000 39
 
0.1%
500 37
 
0.1%
15000 35
 
0.1%
68215.44 33
 
0.1%
3000 31
 
0.1%
20000 30
 
0.1%
Other values (3849) 7588
 
15.2%
ValueCountFrequency (%)
0 41554
83.1%
1 1
 
< 0.1%
1.03 1
 
< 0.1%
2 572
 
1.1%
3 1
 
< 0.1%
ValueCountFrequency (%)
1505584 3
< 0.1%
1250000 5
< 0.1%
1186450.01 3
< 0.1%
928098.23 1
 
< 0.1%
898741 6
< 0.1%

GovtServices_amt_12m
Real number (ℝ)

SKEWED  ZEROS 

Distinct7060
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18016.19656
Minimum0
Maximum15000000
Zeros36573
Zeros (%)73.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.753440image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3300
95-th percentile25266.326
Maximum15000000
Range15000000
Interquartile range (IQR)300

Descriptive statistics

Standard deviation389880.2572
Coefficient of variation (CV)21.64054194
Kurtosis1436.625262
Mean18016.19656
Median Absolute Deviation (MAD)0
Skewness37.52586981
Sum900809827.8
Variance1.52006615 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:33.830060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36573
73.1%
50 113
 
0.2%
1526.55 92
 
0.2%
500 83
 
0.2%
201.76 70
 
0.1%
200 61
 
0.1%
100 53
 
0.1%
1000 45
 
0.1%
50445 43
 
0.1%
2000 41
 
0.1%
Other values (7050) 12826
 
25.7%
ValueCountFrequency (%)
0 36573
73.1%
3.03 2
 
< 0.1%
5.06 3
 
< 0.1%
7 1
 
< 0.1%
8.26 11
 
< 0.1%
ValueCountFrequency (%)
15000000 33
0.1%
2458136 5
 
< 0.1%
2281696.4 1
 
< 0.1%
1654514 1
 
< 0.1%
1594670.03 2
 
< 0.1%

spends_1m
Real number (ℝ)

Distinct33763
Distinct (%)67.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83247.70261
Minimum2500
Maximum8467708.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:33.918488image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile6453.4115
Q119572.735
median40000
Q384194.2375
95-th percentile268910.7525
Maximum8467708.23
Range8465208.23
Interquartile range (IQR)64621.5025

Descriptive statistics

Standard deviation254068.0775
Coefficient of variation (CV)3.051953022
Kurtosis788.5777436
Mean83247.70261
Median Absolute Deviation (MAD)25398
Skewness24.86908428
Sum4162385130
Variance6.455058801 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:33.993886image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25000 56
 
0.1%
15177 48
 
0.1%
20000 41
 
0.1%
50000 41
 
0.1%
30000 38
 
0.1%
25295 38
 
0.1%
10000 37
 
0.1%
60000 35
 
0.1%
1556129.76 34
 
0.1%
8467708.23 33
 
0.1%
Other values (33753) 49599
99.2%
ValueCountFrequency (%)
2500 4
< 0.1%
2502 1
 
< 0.1%
2503.2 1
 
< 0.1%
2504 1
 
< 0.1%
2504.5 1
 
< 0.1%
ValueCountFrequency (%)
8467708.23 33
0.1%
3150571.04 11
 
< 0.1%
2446771 5
 
< 0.1%
2140339.56 5
 
< 0.1%
2030811.5 3
 
< 0.1%

spends_3m
Real number (ℝ)

Distinct35450
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188186.8484
Minimum2500
Maximum17200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.071444image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile14257.664
Q144973.6325
median93108.2
Q3193814.8725
95-th percentile604998.27
Maximum17200000
Range17197500
Interquartile range (IQR)148841.24

Descriptive statistics

Standard deviation532776.4455
Coefficient of variation (CV)2.831103501
Kurtosis692.7758058
Mean188186.8484
Median Absolute Deviation (MAD)59519.595
Skewness22.86820727
Sum9409342421
Variance2.838507409 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:34.149264image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5063763.43 34
 
0.1%
17200000 33
 
0.1%
1626364.36 25
 
0.1%
1611313.95 20
 
< 0.1%
1951245.3 20
 
< 0.1%
1117684.16 19
 
< 0.1%
610512.88 18
 
< 0.1%
50000 16
 
< 0.1%
3901043.97 14
 
< 0.1%
2934583.44 14
 
< 0.1%
Other values (35440) 49787
99.6%
ValueCountFrequency (%)
2500 2
< 0.1%
2502 1
 
< 0.1%
2506 1
 
< 0.1%
2516 1
 
< 0.1%
2529.5 4
< 0.1%
ValueCountFrequency (%)
17200000 33
0.1%
5063763.43 34
0.1%
4912224.63 11
 
< 0.1%
4656142.19 2
 
< 0.1%
4484200 1
 
< 0.1%

spends_6m
Real number (ℝ)

Distinct35450
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188186.8484
Minimum2500
Maximum17200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.228820image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile14257.664
Q144973.6325
median93108.2
Q3193814.8725
95-th percentile604998.27
Maximum17200000
Range17197500
Interquartile range (IQR)148841.24

Descriptive statistics

Standard deviation532776.4455
Coefficient of variation (CV)2.831103501
Kurtosis692.7758058
Mean188186.8484
Median Absolute Deviation (MAD)59519.595
Skewness22.86820727
Sum9409342421
Variance2.838507409 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:34.303459image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5063763.43 34
 
0.1%
17200000 33
 
0.1%
1626364.36 25
 
0.1%
1611313.95 20
 
< 0.1%
1951245.3 20
 
< 0.1%
1117684.16 19
 
< 0.1%
610512.88 18
 
< 0.1%
50000 16
 
< 0.1%
3901043.97 14
 
< 0.1%
2934583.44 14
 
< 0.1%
Other values (35440) 49787
99.6%
ValueCountFrequency (%)
2500 2
< 0.1%
2502 1
 
< 0.1%
2506 1
 
< 0.1%
2516 1
 
< 0.1%
2529.5 4
< 0.1%
ValueCountFrequency (%)
17200000 33
0.1%
5063763.43 34
0.1%
4912224.63 11
 
< 0.1%
4656142.19 2
 
< 0.1%
4484200 1
 
< 0.1%

spends_12m
Real number (ℝ)

Distinct35450
Distinct (%)70.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188186.8484
Minimum2500
Maximum17200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.382317image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2500
5-th percentile14257.664
Q144973.6325
median93108.2
Q3193814.8725
95-th percentile604998.27
Maximum17200000
Range17197500
Interquartile range (IQR)148841.24

Descriptive statistics

Standard deviation532776.4455
Coefficient of variation (CV)2.831103501
Kurtosis692.7758058
Mean188186.8484
Median Absolute Deviation (MAD)59519.595
Skewness22.86820727
Sum9409342421
Variance2.838507409 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:34.455479image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5063763.43 34
 
0.1%
17200000 33
 
0.1%
1626364.36 25
 
0.1%
1611313.95 20
 
< 0.1%
1951245.3 20
 
< 0.1%
1117684.16 19
 
< 0.1%
610512.88 18
 
< 0.1%
50000 16
 
< 0.1%
3901043.97 14
 
< 0.1%
2934583.44 14
 
< 0.1%
Other values (35440) 49787
99.6%
ValueCountFrequency (%)
2500 2
< 0.1%
2502 1
 
< 0.1%
2506 1
 
< 0.1%
2516 1
 
< 0.1%
2529.5 4
< 0.1%
ValueCountFrequency (%)
17200000 33
0.1%
5063763.43 34
0.1%
4912224.63 11
 
< 0.1%
4656142.19 2
 
< 0.1%
4484200 1
 
< 0.1%

revolve_1m
Real number (ℝ)

MISSING  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing3421
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean0.08881684879
Minimum0
Maximum1
Zeros42442
Zeros (%)84.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.519578image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2844822554
Coefficient of variation (CV)3.203021265
Kurtosis6.357410393
Mean0.08881684879
Median Absolute Deviation (MAD)0
Skewness2.890871395
Sum4137
Variance0.08093015365
MonotonicityNot monotonic
2023-04-05T23:08:34.573753image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 42442
84.9%
1 4137
 
8.3%
(Missing) 3421
 
6.8%
ValueCountFrequency (%)
0 42442
84.9%
1 4137
 
8.3%
ValueCountFrequency (%)
1 4137
 
8.3%
0 42442
84.9%

revolve_3m
Real number (ℝ)

MISSING  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing3421
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean0.1399128363
Minimum0
Maximum1
Zeros40062
Zeros (%)80.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.623374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3469002999
Coefficient of variation (CV)2.479402957
Kurtosis2.310356707
Mean0.1399128363
Median Absolute Deviation (MAD)0
Skewness2.076115967
Sum6517
Variance0.1203398181
MonotonicityNot monotonic
2023-04-05T23:08:34.676729image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 40062
80.1%
1 6517
 
13.0%
(Missing) 3421
 
6.8%
ValueCountFrequency (%)
0 40062
80.1%
1 6517
 
13.0%
ValueCountFrequency (%)
1 6517
 
13.0%
0 40062
80.1%

revolve_6m
Real number (ℝ)

MISSING  ZEROS 

Distinct2
Distinct (%)< 0.1%
Missing3421
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean0.1846540286
Minimum0
Maximum1
Zeros37978
Zeros (%)76.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:34.725976image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3880208122
Coefficient of variation (CV)2.101339543
Kurtosis0.6422040445
Mean0.1846540286
Median Absolute Deviation (MAD)0
Skewness1.625477306
Sum8601
Variance0.1505601507
MonotonicityNot monotonic
2023-04-05T23:08:34.777526image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 37978
76.0%
1 8601
 
17.2%
(Missing) 3421
 
6.8%
ValueCountFrequency (%)
0 37978
76.0%
1 8601
 
17.2%
ValueCountFrequency (%)
1 8601
 
17.2%
0 37978
76.0%

util_1m
Real number (ℝ)

MISSING  ZEROS 

Distinct29886
Distinct (%)64.2%
Missing3430
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean0.2861211378
Minimum-4.181810345
Maximum1.220772
Zeros3793
Zeros (%)7.6%
Negative2225
Negative (%)4.5%
Memory size390.8 KiB
2023-04-05T23:08:34.843672image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-4.181810345
5-th percentile0
Q10.0287306565
median0.149961822
Q30.4761
95-th percentile0.980159732
Maximum1.220772
Range5.402582345
Interquartile range (IQR)0.4473693435

Descriptive statistics

Standard deviation0.3288056634
Coefficient of variation (CV)1.149183405
Kurtosis2.799773342
Mean0.2861211378
Median Absolute Deviation (MAD)0.147084572
Skewness0.6630495531
Sum13324.66139
Variance0.1081131643
MonotonicityNot monotonic
2023-04-05T23:08:34.925279image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3793
 
7.6%
1 84
 
0.2%
1.056274067 34
 
0.1%
0.269772235 25
 
0.1%
0.615943517 20
 
< 0.1%
-0.024539025 19
 
< 0.1%
0.0496735 18
 
< 0.1%
0.8422771 14
 
< 0.1%
0.520596875 14
 
< 0.1%
0.16149297 14
 
< 0.1%
Other values (29876) 42535
85.1%
(Missing) 3430
 
6.9%
ValueCountFrequency (%)
-4.181810345 1
 
< 0.1%
-3.779525 3
< 0.1%
-2.845282468 2
< 0.1%
-2.713381296 2
< 0.1%
-2.3833292 1
 
< 0.1%
ValueCountFrequency (%)
1.220772 1
 
< 0.1%
1.165178955 1
 
< 0.1%
1.165122654 1
 
< 0.1%
1.1551125 3
< 0.1%
1.145652444 1
 
< 0.1%

util_3m
Real number (ℝ)

MISSING  ZEROS 

Distinct31718
Distinct (%)68.1%
Missing3421
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean0.2769589456
Minimum-5.621556727
Maximum1.158873067
Zeros1946
Zeros (%)3.9%
Negative1144
Negative (%)2.3%
Memory size390.8 KiB
2023-04-05T23:08:35.090768image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-5.621556727
5-th percentile0
Q10.0510982805
median0.17663
Q30.426151464
95-th percentile0.9230671664
Maximum1.158873067
Range6.780429794
Interquartile range (IQR)0.3750531835

Descriptive statistics

Standard deviation0.290071503
Coefficient of variation (CV)1.047344769
Kurtosis7.441545939
Mean0.2769589456
Median Absolute Deviation (MAD)0.151708867
Skewness0.5467103541
Sum12900.47073
Variance0.08414147684
MonotonicityNot monotonic
2023-04-05T23:08:35.161197image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1946
 
3.9%
1.081001611 34
 
0.1%
1 29
 
0.1%
0.331456043 25
 
0.1%
0.265136133 20
 
< 0.1%
0.547633718 20
 
< 0.1%
0.363157075 19
 
< 0.1%
0.177581911 18
 
< 0.1%
0.733146656 14
 
< 0.1%
0.704857667 14
 
< 0.1%
Other values (31708) 44440
88.9%
(Missing) 3421
 
6.8%
ValueCountFrequency (%)
-5.621556727 1
 
< 0.1%
-4.181810345 1
 
< 0.1%
-3.390836667 3
< 0.1%
-2.8003673 2
< 0.1%
-2.773814444 1
 
< 0.1%
ValueCountFrequency (%)
1.158873067 1
< 0.1%
1.153696914 1
< 0.1%
1.144906133 1
< 0.1%
1.139979568 1
< 0.1%
1.137157861 1
< 0.1%

util_6m
Real number (ℝ)

MISSING  ZEROS 

Distinct32099
Distinct (%)68.9%
Missing3421
Missing (%)6.8%
Infinite0
Infinite (%)0.0%
Mean0.2700630135
Minimum-8.490338472
Maximum1.152833133
Zeros1531
Zeros (%)3.1%
Negative794
Negative (%)1.6%
Memory size390.8 KiB
2023-04-05T23:08:35.240472image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-8.490338472
5-th percentile3.303 × 10-7
Q10.058282991
median0.177386221
Q30.4109363635
95-th percentile0.8864940025
Maximum1.152833133
Range9.643171605
Interquartile range (IQR)0.3526533725

Descriptive statistics

Standard deviation0.2795309849
Coefficient of variation (CV)1.035058379
Kurtosis28.78903012
Mean0.2700630135
Median Absolute Deviation (MAD)0.143645035
Skewness-0.09496150341
Sum12579.26511
Variance0.07813757153
MonotonicityNot monotonic
2023-04-05T23:08:35.312407image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1531
 
3.1%
1.086199475 34
 
0.1%
0.238447588 25
 
0.1%
0.383533107 20
 
< 0.1%
0.442238179 20
 
< 0.1%
0.305775888 19
 
< 0.1%
0.377261272 18
 
< 0.1%
1 17
 
< 0.1%
0.087867973 14
 
< 0.1%
0.7114949 14
 
< 0.1%
Other values (32089) 44867
89.7%
(Missing) 3421
 
6.8%
ValueCountFrequency (%)
-8.490338472 1
 
< 0.1%
-5.621556727 1
 
< 0.1%
-4.181810345 1
 
< 0.1%
-3.390836667 3
< 0.1%
-2.39937097 2
< 0.1%
ValueCountFrequency (%)
1.152833133 1
< 0.1%
1.144906133 1
< 0.1%
1.129983932 1
< 0.1%
1.128258864 1
< 0.1%
1.127980348 1
< 0.1%

payment_ratio_1m
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct24296
Distinct (%)59.1%
Missing8889
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean-311.3116825
Minimum-1019726.19
Maximum319673.2143
Zeros1703
Zeros (%)3.4%
Negative771
Negative (%)1.5%
Memory size390.8 KiB
2023-04-05T23:08:35.385681image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-1019726.19
5-th percentile0
Q10.9999558715
median1
Q31.002440173
95-th percentile2.57296782
Maximum319673.2143
Range1339399.404
Interquartile range (IQR)0.0024843015

Descriptive statistics

Standard deviation14329.98308
Coefficient of variation (CV)-46.03098402
Kurtosis4028.497907
Mean-311.3116825
Median Absolute Deviation (MAD)0.000829822
Skewness-59.29663513
Sum-12798334.58
Variance205348415.1
MonotonicityNot monotonic
2023-04-05T23:08:35.468060image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3648
 
7.3%
0 1703
 
3.4%
2 76
 
0.2%
0.243166324 34
 
0.1%
4.372517434 25
 
0.1%
0.05 23
 
< 0.1%
1.305317073 20
 
< 0.1%
9.346678731 20
 
< 0.1%
5.170529613 19
 
< 0.1%
8.455494849 18
 
< 0.1%
Other values (24286) 35525
71.0%
(Missing) 8889
 
17.8%
ValueCountFrequency (%)
-1019726.19 6
< 0.1%
-712658.3333 1
 
< 0.1%
-625000 1
 
< 0.1%
-401895 1
 
< 0.1%
-354080 1
 
< 0.1%
ValueCountFrequency (%)
319673.2143 1
< 0.1%
286950 1
< 0.1%
146900 1
< 0.1%
81320 1
< 0.1%
70932.43243 1
< 0.1%

payment_ratio_3m
Real number (ℝ)

MISSING  SKEWED 

Distinct28538
Distinct (%)66.4%
Missing6990
Missing (%)14.0%
Infinite0
Infinite (%)0.0%
Mean-619.8010839
Minimum-3704709.524
Maximum270036
Zeros418
Zeros (%)0.8%
Negative778
Negative (%)1.6%
Memory size390.8 KiB
2023-04-05T23:08:35.547816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-3704709.524
5-th percentile0.1270283466
Q10.999977079
median1.000465329
Q31.063867672
95-th percentile3.18013421
Maximum270036
Range3974745.524
Interquartile range (IQR)0.06389059325

Descriptive statistics

Standard deviation44429.15593
Coefficient of variation (CV)-71.68292713
Kurtosis6752.079765
Mean-619.8010839
Median Absolute Deviation (MAD)0.004937279
Skewness-81.408264
Sum-26657644.62
Variance1973949897
MonotonicityNot monotonic
2023-04-05T23:08:35.623988image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1632
 
3.3%
0 418
 
0.8%
-0.5 36
 
0.1%
2.148109717 34
 
0.1%
-1 30
 
0.1%
3.507474759 25
 
0.1%
2 25
 
0.1%
2.228055745 20
 
< 0.1%
2.890307692 20
 
< 0.1%
2.918535661 19
 
< 0.1%
Other values (28528) 40751
81.5%
(Missing) 6990
 
14.0%
ValueCountFrequency (%)
-3704709.524 6
< 0.1%
-1226710 1
 
< 0.1%
-488168.4 2
 
< 0.1%
-269911 4
< 0.1%
-143506.4103 2
 
< 0.1%
ValueCountFrequency (%)
270036 2
< 0.1%
110315.4762 1
< 0.1%
18304.87805 1
< 0.1%
14368.98263 1
< 0.1%
14352.94118 1
< 0.1%

payment_ratio_6m
Real number (ℝ)

MISSING  SKEWED 

Distinct29635
Distinct (%)68.2%
Missing6536
Missing (%)13.1%
Infinite0
Infinite (%)0.0%
Mean-556.4841232
Minimum-3704709.524
Maximum273517
Zeros150
Zeros (%)0.3%
Negative654
Negative (%)1.3%
Memory size390.8 KiB
2023-04-05T23:08:35.706724image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-3704709.524
5-th percentile0.254369267
Q10.9999815575
median1.00108895
Q31.118157603
95-th percentile3.286817109
Maximum273517
Range3978226.524
Interquartile range (IQR)0.1181760455

Descriptive statistics

Standard deviation43669.86947
Coefficient of variation (CV)-78.47460089
Kurtosis7144.14233
Mean-556.4841232
Median Absolute Deviation (MAD)0.0259874135
Skewness-84.26270787
Sum-24187025.93
Variance1907057499
MonotonicityNot monotonic
2023-04-05T23:08:35.781282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1150
 
2.3%
0 150
 
0.3%
2.763527208 34
 
0.1%
-1 30
 
0.1%
3.860469517 25
 
0.1%
2 21
 
< 0.1%
-0.5 20
 
< 0.1%
2.648910934 20
 
< 0.1%
3.40490891 20
 
< 0.1%
4.039124107 19
 
< 0.1%
Other values (29625) 41975
84.0%
(Missing) 6536
 
13.1%
ValueCountFrequency (%)
-3704709.524 6
< 0.1%
-269911 4
< 0.1%
-130887.5 1
 
< 0.1%
-108769 2
 
< 0.1%
-105617.9487 1
 
< 0.1%
ValueCountFrequency (%)
273517 2
< 0.1%
110315.4762 1
< 0.1%
18304.87805 1
< 0.1%
14352.94118 1
< 0.1%
2406.5 1
< 0.1%

paymad_1m
Real number (ℝ)

MISSING  SKEWED 

Distinct22588
Distinct (%)58.2%
Missing11185
Missing (%)22.4%
Infinite0
Infinite (%)0.0%
Mean51.1902387
Minimum0
Maximum319673.2143
Zeros178
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:35.858466image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.000057169
Q111.55
median19.992004
Q320.01497491
95-th percentile43.35855292
Maximum319673.2143
Range319673.2143
Interquartile range (IQR)8.46497491

Descriptive statistics

Standard deviation2409.143773
Coefficient of variation (CV)47.06256181
Kurtosis13588.80013
Mean51.1902387
Median Absolute Deviation (MAD)0.1854704
Skewness111.890308
Sum1986949.115
Variance5803973.718
MonotonicityNot monotonic
2023-04-05T23:08:35.930571image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1224
 
2.4%
20 1006
 
2.0%
0 178
 
0.4%
4.235770207 34
 
0.1%
10 27
 
0.1%
87.44050488 25
 
0.1%
186.9147451 20
 
< 0.1%
26.10634146 20
 
< 0.1%
2 20
 
< 0.1%
103.4088386 19
 
< 0.1%
Other values (22578) 36242
72.5%
(Missing) 11185
 
22.4%
ValueCountFrequency (%)
0 178
0.4%
0.000663 1
 
< 0.1%
0.003040746 1
 
< 0.1%
0.004761905 1
 
< 0.1%
0.021437579 1
 
< 0.1%
ValueCountFrequency (%)
319673.2143 1
< 0.1%
286950 1
< 0.1%
146900 1
< 0.1%
81320 1
< 0.1%
70932.43243 1
< 0.1%

paymad_3m
Real number (ℝ)

MISSING  SKEWED 

Distinct28649
Distinct (%)68.0%
Missing7859
Missing (%)15.7%
Infinite0
Infinite (%)0.0%
Mean2513.665774
Minimum0
Maximum9392446.939
Zeros30
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.006522image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.459793703
Q113.39392095
median19.99218485
Q320.18067118
95-th percentile56.2427157
Maximum9392446.939
Range9392446.939
Interquartile range (IQR)6.78675023

Descriptive statistics

Standard deviation151746.1101
Coefficient of variation (CV)60.36845139
Kurtosis3824.71663
Mean2513.665774
Median Absolute Deviation (MAD)1.93474503
Skewness61.85228678
Sum105928389.4
Variance2.302688193 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:36.077816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 415
 
0.8%
20 393
 
0.8%
26.23494968 34
 
0.1%
0 30
 
0.1%
70.13912232 25
 
0.1%
44.56008243 20
 
< 0.1%
57.80615385 20
 
< 0.1%
58.36842491 19
 
< 0.1%
82.29515526 18
 
< 0.1%
182.731841 14
 
< 0.1%
Other values (28639) 41153
82.3%
(Missing) 7859
 
15.7%
ValueCountFrequency (%)
0 30
0.1%
0.000663 1
 
< 0.1%
0.001996008 1
 
< 0.1%
0.019704433 1
 
< 0.1%
0.098345154 1
 
< 0.1%
ValueCountFrequency (%)
9392446.939 11
< 0.1%
270036 2
 
< 0.1%
156310.2041 1
 
< 0.1%
137200 1
 
< 0.1%
110315.4762 1
 
< 0.1%

paymad_6m
Real number (ℝ)

MISSING  SKEWED 

Distinct30037
Distinct (%)69.9%
Missing7026
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean2510.30696
Minimum0
Maximum9495679.592
Zeros12
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.244272image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.837682801
Q113.81779446
median19.99393974
Q320.76940504
95-th percentile58.27254385
Maximum9495679.592
Range9495679.592
Interquartile range (IQR)6.951610582

Descriptive statistics

Standard deviation151925.8376
Coefficient of variation (CV)60.52082078
Kurtosis3899.797625
Mean2510.30696
Median Absolute Deviation (MAD)2.589786935
Skewness62.45375746
Sum107877931.3
Variance2.308146014 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:36.315416image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20 329
 
0.7%
1 152
 
0.3%
35.97306874 34
 
0.1%
77.19953808 25
 
0.1%
52.97754035 20
 
< 0.1%
68.09817293 20
 
< 0.1%
80.78022959 19
 
< 0.1%
34.46684111 18
 
< 0.1%
34.46245378 14
 
< 0.1%
117.1357747 14
 
< 0.1%
Other values (30027) 42329
84.7%
(Missing) 7026
 
14.1%
ValueCountFrequency (%)
0 12
< 0.1%
0.000663 1
 
< 0.1%
0.001996008 1
 
< 0.1%
0.005698006 2
 
< 0.1%
0.098345154 1
 
< 0.1%
ValueCountFrequency (%)
9495679.592 11
< 0.1%
273517 2
 
< 0.1%
137200 1
 
< 0.1%
130230.7692 6
< 0.1%
110315.4762 1
 
< 0.1%

has_taken_emi_before
Real number (ℝ)

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing39958
Missing (%)79.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.375975image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum10042
Variance0
MonotonicityIncreasing
2023-04-05T23:08:36.422135image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1 10042
 
20.1%
(Missing) 39958
79.9%
ValueCountFrequency (%)
1 10042
20.1%
ValueCountFrequency (%)
1 10042
20.1%

count_of_emi_before
Real number (ℝ)

Distinct44
Distinct (%)0.4%
Missing39958
Missing (%)79.9%
Infinite0
Infinite (%)0.0%
Mean3.186616212
Minimum1
Maximum76
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.490724image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile11
Maximum76
Range75
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.346145797
Coefficient of variation (CV)1.363874878
Kurtosis33.73931695
Mean3.186616212
Median Absolute Deviation (MAD)1
Skewness4.554797965
Sum32000
Variance18.88898329
MonotonicityNot monotonic
2023-04-05T23:08:36.562900image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 4846
 
9.7%
2 1753
 
3.5%
3 931
 
1.9%
4 640
 
1.3%
5 449
 
0.9%
6 278
 
0.6%
7 211
 
0.4%
8 164
 
0.3%
9 140
 
0.3%
11 91
 
0.2%
Other values (34) 539
 
1.1%
(Missing) 39958
79.9%
ValueCountFrequency (%)
1 4846
9.7%
2 1753
 
3.5%
3 931
 
1.9%
4 640
 
1.3%
5 449
 
0.9%
ValueCountFrequency (%)
76 1
 
< 0.1%
69 1
 
< 0.1%
51 1
 
< 0.1%
50 1
 
< 0.1%
44 5
< 0.1%

age
Real number (ℝ)

Distinct12929
Distinct (%)25.9%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-38.25527231
Minimum-81.56989247
Maximum-21.06989247
Zeros0
Zeros (%)0.0%
Negative49998
Negative (%)> 99.9%
Memory size390.8 KiB
2023-04-05T23:08:36.642806image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-81.56989247
5-th percentile-62.86370968
Q1-43.49731183
median-35.30107527
Q3-29.86021505
95-th percentile-25.04569893
Maximum-21.06989247
Range60.5
Interquartile range (IQR)13.63709678

Descriptive statistics

Standard deviation11.40218204
Coefficient of variation (CV)-0.2980551792
Kurtosis0.9360754312
Mean-38.25527231
Median Absolute Deviation (MAD)6.27419355
Skewness-1.159013226
Sum-1912687.105
Variance130.0097553
MonotonicityNot monotonic
2023-04-05T23:08:36.717417image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-34.24731183 52
 
0.1%
-31.24731183 48
 
0.1%
-30.24731183 43
 
0.1%
-29.24731183 41
 
0.1%
-31.82258065 40
 
0.1%
-36.24731183 38
 
0.1%
-44.24731183 38
 
0.1%
-32.24731183 37
 
0.1%
-28.24731183 36
 
0.1%
-26.24731183 35
 
0.1%
Other values (12919) 49590
99.2%
ValueCountFrequency (%)
-81.56989247 1
 
< 0.1%
-81.42741936 1
 
< 0.1%
-81.4139785 1
 
< 0.1%
-81.37634409 3
< 0.1%
-81.37096774 3
< 0.1%
ValueCountFrequency (%)
-21.06989247 1
< 0.1%
-21.10483871 1
< 0.1%
-21.11290323 2
< 0.1%
-21.12903226 1
< 0.1%
-21.1344086 1
< 0.1%

married_flag
Real number (ℝ)

CONSTANT  ZEROS 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0
Minimum0
Maximum0
Zeros50000
Zeros (%)100.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.779276image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum0
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)nan
Kurtosis0
Mean0
Median Absolute Deviation (MAD)0
Skewness0
Sum0
Variance0
MonotonicityIncreasing
2023-04-05T23:08:36.824469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%
ValueCountFrequency (%)
0 50000
100.0%

ASSET_OWNERSHIP
Real number (ℝ)

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.33854
Minimum0
Maximum1
Zeros33073
Zeros (%)66.1%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.874115image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.4732178643
Coefficient of variation (CV)1.39781965
Kurtosis-1.534365524
Mean0.33854
Median Absolute Deviation (MAD)0
Skewness0.6824191174
Sum16927
Variance0.2239351471
MonotonicityNot monotonic
2023-04-05T23:08:36.924992image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
0 33073
66.1%
1 16927
33.9%
ValueCountFrequency (%)
0 33073
66.1%
1 16927
33.9%
ValueCountFrequency (%)
1 16927
33.9%
0 33073
66.1%

Bureau_AL_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct3833
Distinct (%)32.9%
Missing38351
Missing (%)76.7%
Infinite0
Infinite (%)0.0%
Mean1448919.139
Minimum1159
Maximum434000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:36.996430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1159
5-th percentile200000
Q1416154
median696000
Q31250000
95-th percentile4100080
Maximum434000000
Range433998841
Interquartile range (IQR)833846

Descriptive statistics

Standard deviation7786698.725
Coefficient of variation (CV)5.374143054
Kurtosis2571.918557
Mean1448919.139
Median Absolute Deviation (MAD)339062
Skewness47.93700845
Sum1.687845905 × 1010
Variance6.063267704 × 1013
MonotonicityNot monotonic
2023-04-05T23:08:37.071654image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500000 407
 
0.8%
600000 299
 
0.6%
400000 287
 
0.6%
300000 280
 
0.6%
200000 202
 
0.4%
700000 187
 
0.4%
350000 161
 
0.3%
800000 155
 
0.3%
450000 126
 
0.3%
1000000 123
 
0.2%
Other values (3823) 9422
 
18.8%
(Missing) 38351
76.7%
ValueCountFrequency (%)
1159 2
 
< 0.1%
1399 4
< 0.1%
1699 5
< 0.1%
1759 2
 
< 0.1%
1924 6
< 0.1%
ValueCountFrequency (%)
434000000 3
< 0.1%
269000000 1
 
< 0.1%
61500000 2
< 0.1%
50100000 3
< 0.1%
34000000 3
< 0.1%

Bureau_BL_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct1307
Distinct (%)31.3%
Missing45820
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean5839550.772
Minimum1
Maximum1700000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:37.150118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14712.5
Q1100000
median400000
Q32053200
95-th percentile17000000
Maximum1700000000
Range1699999999
Interquartile range (IQR)1953200

Descriptive statistics

Standard deviation40701081.61
Coefficient of variation (CV)6.969899432
Kurtosis798.7289049
Mean5839550.772
Median Absolute Deviation (MAD)357000
Skewness23.55052485
Sum2.440932223 × 1010
Variance1.656578044 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:37.228349image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 228
 
0.5%
100000 140
 
0.3%
300000 111
 
0.2%
200000 103
 
0.2%
500000 93
 
0.2%
150000 87
 
0.2%
1000000 80
 
0.2%
10000 74
 
0.1%
40000 50
 
0.1%
2000000 47
 
0.1%
Other values (1297) 3167
 
6.3%
(Missing) 45820
91.6%
ValueCountFrequency (%)
1 14
< 0.1%
12 2
 
< 0.1%
399 1
 
< 0.1%
2000 10
< 0.1%
3000 9
< 0.1%
ValueCountFrequency (%)
1700000000 1
 
< 0.1%
700000000 2
 
< 0.1%
516000000 5
< 0.1%
400000000 3
< 0.1%
356000000 1
 
< 0.1%

Bureau_CCOD_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct22788
Distinct (%)67.7%
Missing16336
Missing (%)32.7%
Infinite0
Infinite (%)0.0%
Mean960499.7433
Minimum1
Maximum2820000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:37.309206image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19599.3
Q1112663
median328566
Q3765011
95-th percentile2377746.7
Maximum2820000000
Range2819999999
Interquartile range (IQR)652348

Descriptive statistics

Standard deviation16645500.53
Coefficient of variation (CV)17.33004162
Kurtosis24542.14343
Mean960499.7433
Median Absolute Deviation (MAD)255829.5
Skewness147.7545679
Sum3.233426336 × 1010
Variance2.770726878 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:37.388015image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86000 57
 
0.1%
25000 43
 
0.1%
100000 36
 
0.1%
590 30
 
0.1%
300000 28
 
0.1%
66000 26
 
0.1%
1046756 25
 
0.1%
250000 23
 
< 0.1%
200000 21
 
< 0.1%
65000 21
 
< 0.1%
Other values (22778) 33354
66.7%
(Missing) 16336
32.7%
ValueCountFrequency (%)
1 7
< 0.1%
2 4
< 0.1%
3 1
 
< 0.1%
5 5
< 0.1%
7 2
 
< 0.1%
ValueCountFrequency (%)
2820000000 1
 
< 0.1%
611000000 1
 
< 0.1%
451000000 3
< 0.1%
175000000 1
 
< 0.1%
155000000 3
< 0.1%

Bureau_CV_amt_ever
Real number (ℝ)

Distinct406
Distinct (%)52.5%
Missing49226
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean9741787.143
Minimum20000
Maximum340000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:37.463454image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum20000
5-th percentile156950
Q1377000
median750000
Q33224000
95-th percentile48620000
Maximum340000000
Range339980000
Interquartile range (IQR)2847000

Descriptive statistics

Standard deviation33057407.13
Coefficient of variation (CV)3.393361674
Kurtosis38.68366797
Mean9741787.143
Median Absolute Deviation (MAD)474834.5
Skewness5.726713421
Sum7540143249
Variance1.092792166 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:37.626225image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1011627 12
 
< 0.1%
500000 12
 
< 0.1%
300000 12
 
< 0.1%
400000 10
 
< 0.1%
125000 10
 
< 0.1%
11500000 7
 
< 0.1%
250000 7
 
< 0.1%
2090578 7
 
< 0.1%
870000 7
 
< 0.1%
590000 6
 
< 0.1%
Other values (396) 684
 
1.4%
(Missing) 49226
98.5%
ValueCountFrequency (%)
20000 2
< 0.1%
28000 1
 
< 0.1%
30000 3
< 0.1%
48000 1
 
< 0.1%
50000 1
 
< 0.1%
ValueCountFrequency (%)
340000000 1
 
< 0.1%
283000000 3
< 0.1%
232000000 1
 
< 0.1%
166000000 5
< 0.1%
165000000 5
< 0.1%

Bureau_CD_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct8942
Distinct (%)45.5%
Missing30347
Missing (%)60.7%
Infinite0
Infinite (%)0.0%
Mean107474.1102
Minimum5
Maximum81700000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:37.706365image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile2000
Q118379
median54086
Q3123490
95-th percentile341983
Maximum81700000
Range81699995
Interquartile range (IQR)105111

Descriptive statistics

Standard deviation622915.7572
Coefficient of variation (CV)5.795961058
Kurtosis14993.52574
Mean107474.1102
Median Absolute Deviation (MAD)43402
Skewness115.2986889
Sum2112188687
Variance3.880240406 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:37.781892image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 1457
 
2.9%
3000 301
 
0.6%
4000 283
 
0.6%
10000 198
 
0.4%
1500 111
 
0.2%
60000 107
 
0.2%
40000 90
 
0.2%
1000 85
 
0.2%
25000 85
 
0.2%
20000 80
 
0.2%
Other values (8932) 16856
33.7%
(Missing) 30347
60.7%
ValueCountFrequency (%)
5 1
 
< 0.1%
16 2
 
< 0.1%
52 2
 
< 0.1%
108 1
 
< 0.1%
500 12
< 0.1%
ValueCountFrequency (%)
81700000 1
 
< 0.1%
13100000 1
 
< 0.1%
6000000 1
 
< 0.1%
5869871 1
 
< 0.1%
5843000 4
< 0.1%

Bureau_EL_amt_ever
Real number (ℝ)

Distinct814
Distinct (%)31.5%
Missing47414
Missing (%)94.8%
Infinite0
Infinite (%)0.0%
Mean860098.7243
Minimum5700
Maximum10000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:37.861983image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum5700
5-th percentile97555
Q1224000
median400000
Q31000000
95-th percentile3135250
Maximum10000000
Range9994300
Interquartile range (IQR)776000

Descriptive statistics

Standard deviation1142283.72
Coefficient of variation (CV)1.328084425
Kurtosis12.07254879
Mean860098.7243
Median Absolute Deviation (MAD)233000
Skewness3.015763383
Sum2224215301
Variance1.304812097 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:37.938500image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400000 252
 
0.5%
200000 84
 
0.2%
750000 82
 
0.2%
2000000 73
 
0.1%
1500000 67
 
0.1%
300000 63
 
0.1%
1000000 40
 
0.1%
500000 39
 
0.1%
250000 37
 
0.1%
2500000 31
 
0.1%
Other values (804) 1818
 
3.6%
(Missing) 47414
94.8%
ValueCountFrequency (%)
5700 2
< 0.1%
20060 1
< 0.1%
22500 1
< 0.1%
22750 2
< 0.1%
23400 1
< 0.1%
ValueCountFrequency (%)
10000000 1
< 0.1%
9800000 1
< 0.1%
9200000 2
< 0.1%
8000000 1
< 0.1%
7663582 1
< 0.1%

Bureau_GL_amt_ever
Real number (ℝ)

Distinct2228
Distinct (%)50.4%
Missing45582
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean741242.0389
Minimum2
Maximum45200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.015498image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile25000
Q199912.5
median276000
Q3738784
95-th percentile3048776.6
Maximum45200000
Range45199998
Interquartile range (IQR)638871.5

Descriptive statistics

Standard deviation1570530.491
Coefficient of variation (CV)2.118782271
Kurtosis171.3211303
Mean741242.0389
Median Absolute Deviation (MAD)220000
Skewness9.067322323
Sum3274807328
Variance2.466566022 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:38.088270image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 55
 
0.1%
100000 53
 
0.1%
200000 50
 
0.1%
50000 32
 
0.1%
120000 23
 
< 0.1%
40000 23
 
< 0.1%
30000 19
 
< 0.1%
600000 18
 
< 0.1%
71000 17
 
< 0.1%
250000 17
 
< 0.1%
Other values (2218) 4111
 
8.2%
(Missing) 45582
91.2%
ValueCountFrequency (%)
2 1
< 0.1%
305 1
< 0.1%
1000 1
< 0.1%
2400 1
< 0.1%
2513 1
< 0.1%
ValueCountFrequency (%)
45200000 1
 
< 0.1%
18700000 1
 
< 0.1%
16900000 1
 
< 0.1%
15100000 5
< 0.1%
14500000 1
 
< 0.1%

Bureau_HL_amt_ever
Real number (ℝ)

Distinct4731
Distinct (%)35.7%
Missing36745
Missing (%)73.5%
Infinite0
Infinite (%)0.0%
Mean7544590.037
Minimum8043
Maximum655000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.160658image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum8043
5-th percentile649800.2
Q12000000
median3751764
Q37500661
95-th percentile24130000
Maximum655000000
Range654991957
Interquartile range (IQR)5500661

Descriptive statistics

Standard deviation17041766.2
Coefficient of variation (CV)2.258806127
Kurtosis393.0086942
Mean7544590.037
Median Absolute Deviation (MAD)2251764
Skewness14.74716897
Sum1.000035409 × 1011
Variance2.904217953 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:38.233724image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 277
 
0.6%
1500000 217
 
0.4%
2000000 212
 
0.4%
2500000 169
 
0.3%
1000000 128
 
0.3%
5000000 104
 
0.2%
4000000 104
 
0.2%
3500000 95
 
0.2%
1800000 84
 
0.2%
1200000 82
 
0.2%
Other values (4721) 11783
 
23.6%
(Missing) 36745
73.5%
ValueCountFrequency (%)
8043 1
 
< 0.1%
14050 3
< 0.1%
18766 2
< 0.1%
25000 2
< 0.1%
39000 1
 
< 0.1%
ValueCountFrequency (%)
655000000 2
< 0.1%
375000000 1
 
< 0.1%
284000000 4
< 0.1%
257000000 4
< 0.1%
250000000 1
 
< 0.1%

Bureau_PL_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct6299
Distinct (%)36.6%
Missing32769
Missing (%)65.5%
Infinite0
Infinite (%)0.0%
Mean976697.868
Minimum1
Maximum213000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.314213image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5500
Q1109000
median364500
Q31000000
95-th percentile3610432
Maximum213000000
Range212999999
Interquartile range (IQR)891000

Descriptive statistics

Standard deviation3787191.756
Coefficient of variation (CV)3.877546864
Kurtosis2289.082868
Mean976697.868
Median Absolute Deviation (MAD)310990
Skewness42.03517517
Sum1.682948096 × 1010
Variance1.434282139 × 1013
MonotonicityNot monotonic
2023-04-05T23:08:38.388278image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 407
 
0.8%
200000 337
 
0.7%
500000 319
 
0.6%
5000 296
 
0.6%
300000 272
 
0.5%
150000 268
 
0.5%
30000 213
 
0.4%
50000 195
 
0.4%
400000 176
 
0.4%
500 164
 
0.3%
Other values (6289) 14584
29.2%
(Missing) 32769
65.5%
ValueCountFrequency (%)
1 13
 
< 0.1%
140 1
 
< 0.1%
250 2
 
< 0.1%
412 1
 
< 0.1%
500 164
0.3%
ValueCountFrequency (%)
213000000 4
< 0.1%
44000000 4
< 0.1%
38900000 5
< 0.1%
38800000 1
 
< 0.1%
38300000 1
 
< 0.1%

Bureau_LAP_amt_ever
Real number (ℝ)

Distinct1446
Distinct (%)43.5%
Missing46674
Missing (%)93.3%
Infinite0
Infinite (%)0.0%
Mean16584195.02
Minimum1
Maximum1060000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.466799image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile62606.75
Q1509195.5
median1800000
Q36437564.75
95-th percentile59200000
Maximum1060000000
Range1059999999
Interquartile range (IQR)5928369.25

Descriptive statistics

Standard deviation71670524.51
Coefficient of variation (CV)4.321616119
Kurtosis99.8196242
Mean16584195.02
Median Absolute Deviation (MAD)1621065
Skewness9.190381188
Sum5.515903264 × 1010
Variance5.136664084 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:38.549283image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000000 75
 
0.1%
1500000 63
 
0.1%
2000000 52
 
0.1%
2500000 40
 
0.1%
500000 38
 
0.1%
300000 36
 
0.1%
3000000 33
 
0.1%
700000 31
 
0.1%
1200000 30
 
0.1%
800000 28
 
0.1%
Other values (1436) 2900
 
5.8%
(Missing) 46674
93.3%
ValueCountFrequency (%)
1 12
< 0.1%
5220 5
< 0.1%
9590 1
 
< 0.1%
12986 1
 
< 0.1%
13102 1
 
< 0.1%
ValueCountFrequency (%)
1060000000 1
 
< 0.1%
988000000 5
< 0.1%
770000000 6
< 0.1%
717000000 1
 
< 0.1%
691000000 1
 
< 0.1%

Bureau_TW_amt_ever
Real number (ℝ)

Distinct2626
Distinct (%)36.5%
Missing42804
Missing (%)85.6%
Infinite0
Infinite (%)0.0%
Mean84666.09255
Minimum9990
Maximum1810000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.627120image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum9990
5-th percentile27297.75
Q141500
median58500
Q390735.75
95-th percentile192581
Maximum1810000
Range1800010
Interquartile range (IQR)49235.75

Descriptive statistics

Standard deviation117907.3824
Coefficient of variation (CV)1.392616322
Kurtosis92.20556887
Mean84666.09255
Median Absolute Deviation (MAD)20500
Skewness8.436770403
Sum609257202
Variance1.390215083 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:38.793019image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30000 151
 
0.3%
40000 144
 
0.3%
50000 101
 
0.2%
35000 88
 
0.2%
45000 77
 
0.2%
60000 76
 
0.2%
48000 74
 
0.1%
20000 74
 
0.1%
38000 70
 
0.1%
44000 67
 
0.1%
Other values (2616) 6274
 
12.5%
(Missing) 42804
85.6%
ValueCountFrequency (%)
9990 1
 
< 0.1%
10600 1
 
< 0.1%
11000 1
 
< 0.1%
12000 6
< 0.1%
13000 2
 
< 0.1%
ValueCountFrequency (%)
1810000 3
< 0.1%
1750000 3
< 0.1%
1600000 1
 
< 0.1%
1550000 4
< 0.1%
1547675 3
< 0.1%

Bureau_UC_amt_ever
Real number (ℝ)

Distinct738
Distinct (%)49.4%
Missing48507
Missing (%)97.0%
Infinite0
Infinite (%)0.0%
Mean768823.779
Minimum50000
Maximum10200000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:38.871089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum50000
5-th percentile110304.8
Q1250000
median429379
Q3807500
95-th percentile2500000
Maximum10200000
Range10150000
Interquartile range (IQR)557500

Descriptive statistics

Standard deviation1017226.303
Coefficient of variation (CV)1.323094226
Kurtosis20.72586002
Mean768823.779
Median Absolute Deviation (MAD)229379
Skewness3.867477032
Sum1147853902
Variance1.034749351 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:38.948000image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 36
 
0.1%
200000 29
 
0.1%
150000 26
 
0.1%
250000 25
 
0.1%
1000000 16
 
< 0.1%
350000 14
 
< 0.1%
500000 13
 
< 0.1%
800000 13
 
< 0.1%
100000 13
 
< 0.1%
700000 12
 
< 0.1%
Other values (728) 1296
 
2.6%
(Missing) 48507
97.0%
ValueCountFrequency (%)
50000 5
< 0.1%
55000 2
 
< 0.1%
61000 1
 
< 0.1%
63749 1
 
< 0.1%
64482 1
 
< 0.1%
ValueCountFrequency (%)
10200000 1
 
< 0.1%
9000000 3
< 0.1%
8546077 1
 
< 0.1%
7123000 1
 
< 0.1%
5485000 3
< 0.1%

Bureau_unsec_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct8375
Distinct (%)38.1%
Missing27999
Missing (%)56.0%
Infinite0
Infinite (%)0.0%
Mean3048962.736
Minimum1
Maximum1700000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.025776image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7000
Q1150000
median490000
Q31380548
95-th percentile6729000
Maximum1700000000
Range1699999999
Interquartile range (IQR)1230548

Descriptive statistics

Standard deviation30395742.02
Coefficient of variation (CV)9.969207448
Kurtosis1239.948495
Mean3048962.736
Median Absolute Deviation (MAD)420000
Skewness31.55790447
Sum6.708022915 × 1010
Variance9.239011327 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:39.099855image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 415
 
0.8%
150000 390
 
0.8%
50000 359
 
0.7%
200000 320
 
0.6%
500000 316
 
0.6%
300000 300
 
0.6%
400000 284
 
0.6%
5000 217
 
0.4%
30000 182
 
0.4%
1000000 173
 
0.3%
Other values (8365) 19045
38.1%
(Missing) 27999
56.0%
ValueCountFrequency (%)
1 15
< 0.1%
3 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
ValueCountFrequency (%)
1700000000 1
 
< 0.1%
1500000000 1
 
< 0.1%
1140000000 3
< 0.1%
872000000 5
< 0.1%
730000000 2
 
< 0.1%

Bureau_sec_amt_ever
Real number (ℝ)

Distinct5521
Distinct (%)36.3%
Missing34778
Missing (%)69.6%
Infinite0
Infinite (%)0.0%
Mean11890232.3
Minimum1
Maximum1870000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.180029image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile300000
Q11799679.75
median3658351
Q37980000
95-th percentile33000000
Maximum1870000000
Range1869999999
Interquartile range (IQR)6180320.25

Descriptive statistics

Standard deviation58972459.26
Coefficient of variation (CV)4.959739873
Kurtosis429.2885388
Mean11890232.3
Median Absolute Deviation (MAD)2408351
Skewness18.4442372
Sum1.809931161 × 1011
Variance3.477750951 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:39.256460image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 262
 
0.5%
2000000 216
 
0.4%
1500000 207
 
0.4%
2500000 170
 
0.3%
1000000 145
 
0.3%
4000000 103
 
0.2%
5000000 95
 
0.2%
1200000 93
 
0.2%
1800000 92
 
0.2%
3500000 91
 
0.2%
Other values (5511) 13748
 
27.5%
(Missing) 34778
69.6%
ValueCountFrequency (%)
1 7
< 0.1%
200 3
< 0.1%
4500 1
 
< 0.1%
4859 1
 
< 0.1%
7700 1
 
< 0.1%
ValueCountFrequency (%)
1870000000 4
< 0.1%
1260000000 4
< 0.1%
1170000000 5
< 0.1%
1140000000 1
 
< 0.1%
1060000000 1
 
< 0.1%

Bureau_all_amt_ever
Real number (ℝ)

MISSING  SKEWED 

Distinct23965
Distinct (%)62.1%
Missing11400
Missing (%)22.8%
Infinite0
Infinite (%)0.0%
Mean7890301.189
Minimum2
Maximum2820000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.338843image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile37393.2
Q1360691
median1531777
Q35079595
95-th percentile21600000
Maximum2820000000
Range2819999998
Interquartile range (IQR)4718904

Descriptive statistics

Standard deviation54617970.53
Coefficient of variation (CV)6.922165481
Kurtosis807.2848231
Mean7890301.189
Median Absolute Deviation (MAD)1403836.5
Skewness25.67655087
Sum3.045656259 × 1011
Variance2.983122705 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:39.411851image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11700000 78
 
0.2%
2000 73
 
0.1%
10700000 66
 
0.1%
10100000 65
 
0.1%
11500000 64
 
0.1%
11000000 56
 
0.1%
11300000 55
 
0.1%
10200000 54
 
0.1%
11200000 53
 
0.1%
10500000 52
 
0.1%
Other values (23955) 37984
76.0%
(Missing) 11400
 
22.8%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 1
 
< 0.1%
5 3
< 0.1%
6 1
 
< 0.1%
7 2
< 0.1%
ValueCountFrequency (%)
2820000000 1
 
< 0.1%
1880000000 4
< 0.1%
1790000000 5
< 0.1%
1710000000 1
 
< 0.1%
1600000000 5
< 0.1%

Bureau_AL_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct1872
Distinct (%)34.9%
Missing44638
Missing (%)89.3%
Infinite0
Infinite (%)0.0%
Mean1190446.098
Minimum1159
Maximum112000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.489262image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1159
5-th percentile280000
Q1500000
median731940.5
Q31200000
95-th percentile3343850
Maximum112000000
Range111998841
Interquartile range (IQR)700000

Descriptive statistics

Standard deviation2158350.132
Coefficient of variation (CV)1.813059941
Kurtosis1307.382541
Mean1190446.098
Median Absolute Deviation (MAD)268454
Skewness27.28540456
Sum6383171975
Variance4.658475291 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:39.564753image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
500000 200
 
0.4%
600000 158
 
0.3%
800000 130
 
0.3%
700000 127
 
0.3%
400000 112
 
0.2%
1000000 108
 
0.2%
900000 61
 
0.1%
750000 57
 
0.1%
450000 56
 
0.1%
350000 55
 
0.1%
Other values (1862) 4298
 
8.6%
(Missing) 44638
89.3%
ValueCountFrequency (%)
1159 2
 
< 0.1%
1399 4
< 0.1%
1699 5
< 0.1%
1759 2
 
< 0.1%
1924 5
< 0.1%
ValueCountFrequency (%)
112000000 1
 
< 0.1%
22400000 1
 
< 0.1%
20600000 3
< 0.1%
20500000 2
< 0.1%
16400000 3
< 0.1%

Bureau_BL_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct749
Distinct (%)31.5%
Missing47622
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean5414476.273
Minimum1
Maximum1500000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.641698image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10000
Q175000
median500000
Q32500000
95-th percentile14415000
Maximum1500000000
Range1499999999
Interquartile range (IQR)2425000

Descriptive statistics

Standard deviation40767083.2
Coefficient of variation (CV)7.529275437
Kurtosis797.1597993
Mean5414476.273
Median Absolute Deviation (MAD)480000
Skewness24.58258982
Sum1.287562458 × 1010
Variance1.661955073 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:39.715282image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 199
 
0.4%
10000 92
 
0.2%
200000 68
 
0.1%
100000 61
 
0.1%
500000 60
 
0.1%
1000000 57
 
0.1%
40000 45
 
0.1%
300000 44
 
0.1%
2000000 37
 
0.1%
250000 32
 
0.1%
Other values (739) 1683
 
3.4%
(Missing) 47622
95.2%
ValueCountFrequency (%)
1 13
< 0.1%
12 2
 
< 0.1%
2000 5
 
< 0.1%
3000 9
< 0.1%
3300 1
 
< 0.1%
ValueCountFrequency (%)
1500000000 1
 
< 0.1%
436000000 5
< 0.1%
400000000 3
< 0.1%
250000000 1
 
< 0.1%
185000000 1
 
< 0.1%

Bureau_CCOD_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct21696
Distinct (%)67.3%
Missing17781
Missing (%)35.6%
Infinite0
Infinite (%)0.0%
Mean728838.5313
Minimum1
Maximum1330000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.801069image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22193.7
Q1100899.5
median265356
Q3604919.5
95-th percentile1852002.9
Maximum1330000000
Range1329999999
Interquartile range (IQR)504020

Descriptive statistics

Standard deviation9572097.461
Coefficient of variation (CV)13.13335815
Kurtosis12485.85803
Mean728838.5313
Median Absolute Deviation (MAD)197887
Skewness101.0823389
Sum2.348244864 × 1010
Variance9.162504981 × 1013
MonotonicityNot monotonic
2023-04-05T23:08:39.910875image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
86000 99
 
0.2%
100000 42
 
0.1%
25000 41
 
0.1%
66000 33
 
0.1%
300000 33
 
0.1%
500000 27
 
0.1%
120000 27
 
0.1%
250000 25
 
0.1%
888854 25
 
0.1%
65000 22
 
< 0.1%
Other values (21686) 31845
63.7%
(Missing) 17781
35.6%
ValueCountFrequency (%)
1 2
< 0.1%
2 1
< 0.1%
5 2
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
1330000000 1
 
< 0.1%
601000000 1
 
< 0.1%
451000000 3
< 0.1%
175000000 1
 
< 0.1%
121000000 3
< 0.1%

Bureau_CV_amt_live
Real number (ℝ)

Distinct208
Distinct (%)56.1%
Missing49629
Missing (%)99.3%
Infinite0
Infinite (%)0.0%
Mean10314265.55
Minimum30000
Maximum203000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:39.993098image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum30000
5-th percentile186554.5
Q1500000
median1011627
Q34498000
95-th percentile58000000
Maximum203000000
Range202970000
Interquartile range (IQR)3998000

Descriptive statistics

Standard deviation27397556.9
Coefficient of variation (CV)2.656278023
Kurtosis22.61079936
Mean10314265.55
Median Absolute Deviation (MAD)666627
Skewness4.410447583
Sum3826592519
Variance7.506261242 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:40.166398image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1011627 12
 
< 0.1%
500000 8
 
< 0.1%
511578 7
 
< 0.1%
300000 6
 
< 0.1%
104000000 6
 
< 0.1%
1664394 6
 
< 0.1%
17700000 6
 
< 0.1%
630000 5
 
< 0.1%
98500000 5
 
< 0.1%
58000000 5
 
< 0.1%
Other values (198) 305
 
0.6%
(Missing) 49629
99.3%
ValueCountFrequency (%)
30000 3
< 0.1%
90000 2
< 0.1%
100000 1
 
< 0.1%
125000 2
< 0.1%
150000 1
 
< 0.1%
ValueCountFrequency (%)
203000000 3
< 0.1%
125000000 1
 
< 0.1%
119000000 1
 
< 0.1%
104000000 6
< 0.1%
98500000 5
< 0.1%

Bureau_CD_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct2783
Distinct (%)26.6%
Missing39553
Missing (%)79.1%
Infinite0
Infinite (%)0.0%
Mean38549.79295
Minimum750
Maximum5843000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:40.247153image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum750
5-th percentile2000
Q13000
median16790
Q343989
95-th percentile131312
Maximum5843000
Range5842250
Interquartile range (IQR)40989

Descriptive statistics

Standard deviation134409.3429
Coefficient of variation (CV)3.486642407
Kurtosis1354.196922
Mean38549.79295
Median Absolute Deviation (MAD)14790
Skewness32.80678197
Sum402729687
Variance1.806587146 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:40.323327image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 2322
 
4.6%
3000 413
 
0.8%
10000 401
 
0.8%
4000 383
 
0.8%
1500 137
 
0.3%
60000 119
 
0.2%
20000 96
 
0.2%
25000 93
 
0.2%
1000 90
 
0.2%
40000 89
 
0.2%
Other values (2773) 6304
 
12.6%
(Missing) 39553
79.1%
ValueCountFrequency (%)
750 9
 
< 0.1%
917 1
 
< 0.1%
945 1
 
< 0.1%
1000 90
0.2%
1045 2
 
< 0.1%
ValueCountFrequency (%)
5843000 4
< 0.1%
2000000 5
< 0.1%
1500000 1
 
< 0.1%
1000000 3
< 0.1%
950000 1
 
< 0.1%

Bureau_EL_amt_live
Real number (ℝ)

Distinct316
Distinct (%)40.3%
Missing49215
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean1200759.361
Minimum5000
Maximum10000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:40.402489image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum5000
5-th percentile128500
Q1308000
median580000
Q31630000
95-th percentile4000000
Maximum10000000
Range9995000
Interquartile range (IQR)1322000

Descriptive statistics

Standard deviation1373062.278
Coefficient of variation (CV)1.143494961
Kurtosis5.858470713
Mean1200759.361
Median Absolute Deviation (MAD)381706
Skewness2.101772023
Sum942596098
Variance1.88530002 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:40.483767image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
400000 74
 
0.1%
750000 33
 
0.1%
2000000 29
 
0.1%
4000000 25
 
0.1%
500000 20
 
< 0.1%
1500000 17
 
< 0.1%
3000000 16
 
< 0.1%
600000 13
 
< 0.1%
200000 12
 
< 0.1%
1000000 11
 
< 0.1%
Other values (306) 535
 
1.1%
(Missing) 49215
98.4%
ValueCountFrequency (%)
5000 1
< 0.1%
20060 1
< 0.1%
25000 1
< 0.1%
35000 1
< 0.1%
39300 1
< 0.1%
ValueCountFrequency (%)
10000000 1
< 0.1%
9200000 2
< 0.1%
6800000 1
< 0.1%
6078446 2
< 0.1%
6000000 1
< 0.1%

Bureau_GL_amt_live
Real number (ℝ)

Distinct762
Distinct (%)49.0%
Missing48446
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean375067.6641
Minimum305
Maximum5625000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:40.566845image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum305
5-th percentile25000
Q180000
median200000
Q3434200
95-th percentile1273875.5
Maximum5625000
Range5624695
Interquartile range (IQR)354200

Descriptive statistics

Standard deviation563987.9222
Coefficient of variation (CV)1.503696469
Kurtosis34.69941608
Mean375067.6641
Median Absolute Deviation (MAD)148050
Skewness4.867679428
Sum582855150
Variance3.180823763 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:40.640770image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100000 43
 
0.1%
200000 28
 
0.1%
300000 26
 
0.1%
500000 13
 
< 0.1%
270000 12
 
< 0.1%
30000 12
 
< 0.1%
250000 12
 
< 0.1%
78000 12
 
< 0.1%
35000 11
 
< 0.1%
50000 11
 
< 0.1%
Other values (752) 1374
 
2.7%
(Missing) 48446
96.9%
ValueCountFrequency (%)
305 1
< 0.1%
4900 1
< 0.1%
7000 1
< 0.1%
7300 1
< 0.1%
7440 1
< 0.1%
ValueCountFrequency (%)
5625000 5
< 0.1%
5407000 1
 
< 0.1%
4800000 1
 
< 0.1%
4309000 1
 
< 0.1%
3899000 1
 
< 0.1%

Bureau_HL_amt_live
Real number (ℝ)

Distinct3186
Distinct (%)36.2%
Missing41205
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean5578534.705
Minimum18766
Maximum202000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:40.721492image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum18766
5-th percentile900000
Q12000000
median3310077
Q36000000
95-th percentile15500000
Maximum202000000
Range201981234
Interquartile range (IQR)4000000

Descriptive statistics

Standard deviation9095932.15
Coefficient of variation (CV)1.630523539
Kurtosis133.7804704
Mean5578534.705
Median Absolute Deviation (MAD)1658377
Skewness9.062783002
Sum4.906321273 × 1010
Variance8.273598168 × 1013
MonotonicityNot monotonic
2023-04-05T23:08:40.811524image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 249
 
0.5%
2500000 142
 
0.3%
1500000 140
 
0.3%
2000000 126
 
0.3%
4000000 99
 
0.2%
5000000 94
 
0.2%
6000000 88
 
0.2%
3500000 86
 
0.2%
1000000 84
 
0.2%
7500000 72
 
0.1%
Other values (3176) 7615
 
15.2%
(Missing) 41205
82.4%
ValueCountFrequency (%)
18766 2
< 0.1%
48000 1
 
< 0.1%
54000 2
< 0.1%
65000 1
 
< 0.1%
90000 3
< 0.1%
ValueCountFrequency (%)
202000000 4
< 0.1%
120000000 1
 
< 0.1%
116000000 2
< 0.1%
104000000 4
< 0.1%
91000000 3
< 0.1%

Bureau_PL_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct3957
Distinct (%)33.5%
Missing38188
Missing (%)76.4%
Infinite0
Infinite (%)0.0%
Mean595760.0461
Minimum1
Maximum50000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:40.893745image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4000
Q175000
median300000
Q3722000
95-th percentile2000000
Maximum50000000
Range49999999
Interquartile range (IQR)647000

Descriptive statistics

Standard deviation1507184.04
Coefficient of variation (CV)2.529850819
Kurtosis659.530184
Mean595760.0461
Median Absolute Deviation (MAD)260927.5
Skewness22.16304126
Sum7037117664
Variance2.271603731 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:40.975476image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 351
 
0.7%
500000 283
 
0.6%
200000 236
 
0.5%
30000 234
 
0.5%
500 218
 
0.4%
1000000 193
 
0.4%
100000 180
 
0.4%
7000 178
 
0.4%
300000 172
 
0.3%
400000 142
 
0.3%
Other values (3947) 9625
 
19.2%
(Missing) 38188
76.4%
ValueCountFrequency (%)
1 18
< 0.1%
2 1
 
< 0.1%
140 1
 
< 0.1%
250 3
 
< 0.1%
346 2
 
< 0.1%
ValueCountFrequency (%)
50000000 4
< 0.1%
44000000 4
< 0.1%
38300000 1
 
< 0.1%
19000000 1
 
< 0.1%
14100000 1
 
< 0.1%

Bureau_LAP_amt_live
Real number (ℝ)

Distinct1077
Distinct (%)46.7%
Missing47695
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean11557042.63
Minimum1
Maximum732000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.058548image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile58730
Q1458000
median1775281
Q35815000
95-th percentile49000000
Maximum732000000
Range731999999
Interquartile range (IQR)5357000

Descriptive statistics

Standard deviation43470121.76
Coefficient of variation (CV)3.761353414
Kurtosis112.6522967
Mean11557042.63
Median Absolute Deviation (MAD)1600878
Skewness9.595403949
Sum2.663898327 × 1010
Variance1.889651486 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:41.134871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000000 50
 
0.1%
2000000 41
 
0.1%
2500000 31
 
0.1%
1500000 30
 
0.1%
3000000 29
 
0.1%
500000 28
 
0.1%
1200000 22
 
< 0.1%
300000 21
 
< 0.1%
7000000 20
 
< 0.1%
600000 19
 
< 0.1%
Other values (1067) 2014
 
4.0%
(Missing) 47695
95.4%
ValueCountFrequency (%)
1 1
 
< 0.1%
5220 5
< 0.1%
12986 1
 
< 0.1%
13102 1
 
< 0.1%
14000 1
 
< 0.1%
ValueCountFrequency (%)
732000000 1
 
< 0.1%
521000000 5
< 0.1%
513000000 5
< 0.1%
287000000 1
 
< 0.1%
268000000 1
 
< 0.1%

Bureau_TW_amt_live
Real number (ℝ)

Distinct1044
Distinct (%)50.6%
Missing47935
Missing (%)95.9%
Infinite0
Infinite (%)0.0%
Mean94387.1201
Minimum9990
Maximum1550000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.215575image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum9990
5-th percentile30000
Q154000
median69091
Q399000
95-th percentile194988.8
Maximum1550000
Range1540010
Interquartile range (IQR)45000

Descriptive statistics

Standard deviation118748.2311
Coefficient of variation (CV)1.258097831
Kurtosis75.13156044
Mean94387.1201
Median Absolute Deviation (MAD)18592
Skewness7.743704397
Sum194909403
Variance1.410114238 × 1010
MonotonicityNot monotonic
2023-04-05T23:08:41.420701image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 26
 
0.1%
60000 25
 
0.1%
80000 22
 
< 0.1%
20000 20
 
< 0.1%
52000 16
 
< 0.1%
40000 16
 
< 0.1%
65000 16
 
< 0.1%
54000 16
 
< 0.1%
35000 15
 
< 0.1%
56000 15
 
< 0.1%
Other values (1034) 1878
 
3.8%
(Missing) 47935
95.9%
ValueCountFrequency (%)
9990 1
 
< 0.1%
12000 5
< 0.1%
13000 3
< 0.1%
14290 2
 
< 0.1%
15000 1
 
< 0.1%
ValueCountFrequency (%)
1550000 4
< 0.1%
1400000 1
 
< 0.1%
1269000 2
< 0.1%
1100000 3
< 0.1%
1000000 1
 
< 0.1%

Bureau_UC_amt_live
Real number (ℝ)

Distinct429
Distinct (%)57.4%
Missing49252
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean799478.5655
Minimum50000
Maximum9000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.500350image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum50000
5-th percentile129862.5
Q1300000
median504934.5
Q3855769
95-th percentile2423500
Maximum9000000
Range8950000
Interquartile range (IQR)555769

Descriptive statistics

Standard deviation984465.0667
Coefficient of variation (CV)1.231383941
Kurtosis24.67405462
Mean799478.5655
Median Absolute Deviation (MAD)254172.5
Skewness4.137147585
Sum598009967
Variance9.691714676 × 1011
MonotonicityNot monotonic
2023-04-05T23:08:41.576514image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300000 18
 
< 0.1%
855769 12
 
< 0.1%
150000 11
 
< 0.1%
700000 9
 
< 0.1%
233321 9
 
< 0.1%
600000 8
 
< 0.1%
400000 8
 
< 0.1%
1000000 8
 
< 0.1%
170000 7
 
< 0.1%
200000 7
 
< 0.1%
Other values (419) 651
 
1.3%
(Missing) 49252
98.5%
ValueCountFrequency (%)
50000 2
< 0.1%
55000 2
< 0.1%
61000 1
< 0.1%
65000 2
< 0.1%
68826 1
< 0.1%
ValueCountFrequency (%)
9000000 3
< 0.1%
7917623 1
 
< 0.1%
4950000 1
 
< 0.1%
4796275 1
 
< 0.1%
4532500 5
< 0.1%

Bureau_unsec_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct5077
Distinct (%)34.5%
Missing35278
Missing (%)70.6%
Infinite0
Infinite (%)0.0%
Mean2192049.927
Minimum1
Maximum1500000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.648398image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5000
Q1100000
median395941
Q31000000
95-th percentile4200000
Maximum1500000000
Range1499999999
Interquartile range (IQR)900000

Descriptive statistics

Standard deviation22048981.81
Coefficient of variation (CV)10.05861297
Kurtosis1762.510063
Mean2192049.927
Median Absolute Deviation (MAD)345941
Skewness35.10120566
Sum3.227135902 × 1010
Variance4.861575991 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:41.724420image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000 387
 
0.8%
500000 303
 
0.6%
5000 279
 
0.6%
200000 253
 
0.5%
30000 226
 
0.5%
100000 221
 
0.4%
1000000 212
 
0.4%
300000 188
 
0.4%
500 184
 
0.4%
400000 172
 
0.3%
Other values (5067) 12297
 
24.6%
(Missing) 35278
70.6%
ValueCountFrequency (%)
1 21
< 0.1%
2 1
 
< 0.1%
3 2
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
1500000000 1
 
< 0.1%
678000000 1
 
< 0.1%
534000000 5
< 0.1%
512000000 1
 
< 0.1%
508000000 5
< 0.1%

Bureau_sec_amt_live
Real number (ℝ)

Distinct3850
Distinct (%)37.7%
Missing39799
Missing (%)79.6%
Infinite0
Infinite (%)0.0%
Mean8483748.661
Minimum1
Maximum898000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.808294image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile600000
Q11960000
median3400000
Q36441810
95-th percentile23200000
Maximum898000000
Range897999999
Interquartile range (IQR)4481810

Descriptive statistics

Standard deviation34847229.18
Coefficient of variation (CV)4.107527293
Kurtosis375.3989899
Mean8483748.661
Median Absolute Deviation (MAD)1838563
Skewness17.57908841
Sum8.654272009 × 1010
Variance1.214329381 × 1015
MonotonicityNot monotonic
2023-04-05T23:08:41.881051image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000000 246
 
0.5%
2000000 164
 
0.3%
1500000 137
 
0.3%
2500000 134
 
0.3%
4000000 105
 
0.2%
1000000 98
 
0.2%
3500000 93
 
0.2%
5000000 86
 
0.2%
6000000 83
 
0.2%
7500000 73
 
0.1%
Other values (3840) 8982
 
18.0%
(Missing) 39799
79.6%
ValueCountFrequency (%)
1 7
< 0.1%
100 2
 
< 0.1%
200 1
 
< 0.1%
1000 1
 
< 0.1%
4859 1
 
< 0.1%
ValueCountFrequency (%)
898000000 5
< 0.1%
782000000 4
< 0.1%
732000000 1
 
< 0.1%
553000000 5
< 0.1%
521000000 5
< 0.1%

Bureau_all_amt_live
Real number (ℝ)

MISSING  SKEWED 

Distinct23478
Distinct (%)64.2%
Missing13450
Missing (%)26.9%
Infinite0
Infinite (%)0.0%
Mean4121672.237
Minimum2
Maximum1510000000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:41.954637image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile27631.4
Q1199671
median773284
Q32858976
95-th percentile11500000
Maximum1510000000
Range1509999998
Interquartile range (IQR)2659305

Descriptive statistics

Standard deviation30300544.41
Coefficient of variation (CV)7.351517216
Kurtosis1363.223309
Mean4121672.237
Median Absolute Deviation (MAD)694316.5
Skewness33.13915118
Sum1.506471203 × 1011
Variance9.181229914 × 1014
MonotonicityNot monotonic
2023-04-05T23:08:42.028011image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2000 115
 
0.2%
86000 65
 
0.1%
200000 53
 
0.1%
50000 50
 
0.1%
100000 49
 
0.1%
300000 48
 
0.1%
250000 45
 
0.1%
500000 44
 
0.1%
25000 41
 
0.1%
13100000 34
 
0.1%
Other values (23468) 36006
72.0%
(Missing) 13450
 
26.9%
ValueCountFrequency (%)
2 1
< 0.1%
5 2
< 0.1%
6 1
< 0.1%
9 1
< 0.1%
11 2
< 0.1%
ValueCountFrequency (%)
1510000000 1
 
< 0.1%
1490000000 5
< 0.1%
1330000000 1
 
< 0.1%
1040000000 5
< 0.1%
790000000 4
< 0.1%

avg_sa_balance_1m
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct31266
Distinct (%)66.7%
Missing3108
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean508225.2531
Minimum0
Maximum243000000
Zeros2473
Zeros (%)4.9%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:42.114342image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15433.555556
median32687.20666
Q3185024.3161
95-th percentile1983424.403
Maximum243000000
Range243000000
Interquartile range (IQR)179590.7605

Descriptive statistics

Standard deviation3523718.791
Coefficient of variation (CV)6.933379972
Kurtosis2233.806725
Mean508225.2531
Median Absolute Deviation (MAD)32250.97185
Skewness38.79019486
Sum2.383169857 × 1010
Variance1.241659412 × 1013
MonotonicityNot monotonic
2023-04-05T23:08:42.196831image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2473
 
4.9%
1 145
 
0.3%
2 43
 
0.1%
12965.41889 34
 
0.1%
164060.7844 33
 
0.1%
49815.79444 25
 
0.1%
4 22
 
< 0.1%
130041.4822 20
 
< 0.1%
137712.3333 20
 
< 0.1%
10100000 19
 
< 0.1%
Other values (31256) 44058
88.1%
(Missing) 3108
 
6.2%
ValueCountFrequency (%)
0 2473
4.9%
0.005555556 1
 
< 0.1%
0.037037037 2
 
< 0.1%
0.05 2
 
< 0.1%
0.07 2
 
< 0.1%
ValueCountFrequency (%)
243000000 4
< 0.1%
169000000 1
 
< 0.1%
133000000 2
< 0.1%
102000000 3
< 0.1%
100000000 1
 
< 0.1%

avg_sa_balance_3m
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct31496
Distinct (%)67.2%
Missing3108
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean497111.9596
Minimum0
Maximum159000000
Zeros2366
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:42.271441image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17518.413941
median38386.13271
Q3204790.5306
95-th percentile2022022.736
Maximum159000000
Range159000000
Interquartile range (IQR)197272.1167

Descriptive statistics

Standard deviation2701164.307
Coefficient of variation (CV)5.433714186
Kurtosis777.1710369
Mean497111.9596
Median Absolute Deviation (MAD)37521.85506
Skewness22.52760448
Sum2.331057401 × 1010
Variance7.296288612 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:42.351081image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2366
 
4.7%
1 112
 
0.2%
2 37
 
0.1%
37025.42482 34
 
0.1%
95455.664 33
 
0.1%
42613.96918 25
 
0.1%
10100000 23
 
< 0.1%
164278.8129 20
 
< 0.1%
266134.3882 20
 
< 0.1%
26162.91765 19
 
< 0.1%
Other values (31486) 44203
88.4%
(Missing) 3108
 
6.2%
ValueCountFrequency (%)
0 2366
4.7%
0.001764706 1
 
< 0.1%
0.011764706 5
 
< 0.1%
0.023529412 3
 
< 0.1%
0.035294118 2
 
< 0.1%
ValueCountFrequency (%)
159000000 1
 
< 0.1%
112000000 4
< 0.1%
94400000 1
 
< 0.1%
91500000 3
< 0.1%
85500000 2
< 0.1%

avg_sa_balance_6m
Real number (ℝ)

MISSING  ZEROS 

Distinct31877
Distinct (%)68.0%
Missing3108
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean494779.6823
Minimum0
Maximum136000000
Zeros1679
Zeros (%)3.4%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:42.433453image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.3365
Q19299.675762
median44339.34057
Q3228442.892
95-th percentile2043398.206
Maximum136000000
Range136000000
Interquartile range (IQR)219143.2163

Descriptive statistics

Standard deviation2404561.589
Coefficient of variation (CV)4.859863238
Kurtosis583.8109546
Mean494779.6823
Median Absolute Deviation (MAD)42935.77693
Skewness19.3149992
Sum2.320120886 × 1010
Variance5.781916436 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:42.520423image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1679
 
3.4%
1 100
 
0.2%
577687.2443 34
 
0.1%
0.068965517 34
 
0.1%
136778.2796 33
 
0.1%
2 31
 
0.1%
0.022988506 28
 
0.1%
31698.81914 25
 
0.1%
136500.1034 20
 
< 0.1%
0.005747126 20
 
< 0.1%
Other values (31867) 44888
89.8%
(Missing) 3108
 
6.2%
ValueCountFrequency (%)
0 1679
3.4%
0.004712644 1
 
< 0.1%
0.005402299 1
 
< 0.1%
0.005747126 20
 
< 0.1%
0.005977011 1
 
< 0.1%
ValueCountFrequency (%)
136000000 1
 
< 0.1%
90000000 2
< 0.1%
88600000 1
 
< 0.1%
66500000 3
< 0.1%
65600000 4
< 0.1%

avg_sa_balance_12m
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct32420
Distinct (%)69.1%
Missing3108
Missing (%)6.2%
Infinite0
Infinite (%)0.0%
Mean527503.0784
Minimum0
Maximum113000000
Zeros988
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size390.8 KiB
2023-04-05T23:08:42.683990image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30.89050829
Q110838.19955
median55298.39371
Q3281237.1243
95-th percentile2188972.543
Maximum113000000
Range113000000
Interquartile range (IQR)270398.9248

Descriptive statistics

Standard deviation2605561.285
Coefficient of variation (CV)4.939423847
Kurtosis771.671715
Mean527503.0784
Median Absolute Deviation (MAD)53736.95907
Skewness23.02572902
Sum2.473567435 × 1010
Variance6.788949608 × 1012
MonotonicityNot monotonic
2023-04-05T23:08:42.755181image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 988
 
2.0%
1 92
 
0.2%
1489448.266 34
 
0.1%
136778.2796 33
 
0.1%
0.513812155 30
 
0.1%
2 29
 
0.1%
17519.49881 25
 
0.1%
153476.5359 20
 
< 0.1%
289510.4753 20
 
< 0.1%
1.016574586 19
 
< 0.1%
Other values (32410) 45602
91.2%
(Missing) 3108
 
6.2%
ValueCountFrequency (%)
0 988
2.0%
0.011049724 5
 
< 0.1%
0.022038567 1
 
< 0.1%
0.05801105 1
 
< 0.1%
0.08 9
 
< 0.1%
ValueCountFrequency (%)
113000000 3
< 0.1%
110000000 4
< 0.1%
107000000 1
 
< 0.1%
91400000 2
< 0.1%
79300000 1
 
< 0.1%

pctchg_curr_sa_bal_avg_sa_bal_1m
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct30948
Distinct (%)69.8%
Missing5667
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean29.72790006
Minimum-1
Maximum245680.5556
Zeros757
Zeros (%)1.5%
Negative22487
Negative (%)45.0%
Memory size390.8 KiB
2023-04-05T23:08:42.827815image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.825930009
Q1-0.332234279
median-0.002082588
Q30.304482789
95-th percentile4.179775112
Maximum245680.5556
Range245681.5556
Interquartile range (IQR)0.636717068

Descriptive statistics

Standard deviation1887.02075
Coefficient of variation (CV)63.47642269
Kurtosis13367.60071
Mean29.72790006
Median Absolute Deviation (MAD)0.32248091
Skewness108.9881541
Sum1317926.993
Variance3560847.31
MonotonicityNot monotonic
2023-04-05T23:08:42.904152image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 757
 
1.5%
-1 58
 
0.1%
-0.476062942 34
 
0.1%
1.317087839 33
 
0.1%
0.068267752 25
 
0.1%
-0.37172675 20
 
< 0.1%
-0.642494611 20
 
< 0.1%
0.003292122 19
 
< 0.1%
0.074074074 18
 
< 0.1%
-1.39 × 10-1618
 
< 0.1%
Other values (30938) 43331
86.7%
(Missing) 5667
 
11.3%
ValueCountFrequency (%)
-1 58
0.1%
-0.999900467 1
 
< 0.1%
-0.999790731 1
 
< 0.1%
-0.999769654 1
 
< 0.1%
-0.999746436 1
 
< 0.1%
ValueCountFrequency (%)
245680.5556 2
< 0.1%
93443.44444 1
< 0.1%
92830.53333 1
< 0.1%
75327.25543 2
< 0.1%
56374.40777 1
< 0.1%

pctchg_curr_sa_bal_avg_sa_bal_3m
Real number (ℝ)

MISSING  SKEWED 

Distinct30680
Distinct (%)69.4%
Missing5808
Missing (%)11.6%
Infinite0
Infinite (%)0.0%
Mean577.7793082
Minimum-1
Maximum8859915.351
Zeros460
Zeros (%)0.9%
Negative23285
Negative (%)46.6%
Memory size390.8 KiB
2023-04-05T23:08:42.982056image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.8881301643
Q1-0.426054083
median-0.0289204655
Q30.430959657
95-th percentile4.476672642
Maximum8859915.351
Range8859916.351
Interquartile range (IQR)0.85701374

Descriptive statistics

Standard deviation60381.76369
Coefficient of variation (CV)104.5066219
Kurtosis20790.76119
Mean577.7793082
Median Absolute Deviation (MAD)0.41691973
Skewness142.5027904
Sum25533223.19
Variance3645957386
MonotonicityNot monotonic
2023-04-05T23:08:43.056606image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 687
 
1.4%
0 460
 
0.9%
-0.966157455 34
 
0.1%
-0.508869273 33
 
0.1%
1.003078554 25
 
0.1%
0.493852862 20
 
< 0.1%
-0.217869822 20
 
< 0.1%
0.003520403 19
 
< 0.1%
-0.483231694 14
 
< 0.1%
0.517520217 14
 
< 0.1%
Other values (30670) 42866
85.7%
(Missing) 5808
 
11.6%
ValueCountFrequency (%)
-1 687
1.4%
-0.999994521 1
 
< 0.1%
-0.999993291 2
 
< 0.1%
-0.99998816 2
 
< 0.1%
-0.999975741 1
 
< 0.1%
ValueCountFrequency (%)
8859915.351 1
 
< 0.1%
8818411.381 1
 
< 0.1%
1579961.933 1
 
< 0.1%
912017.8 1
 
< 0.1%
492674.2781 3
< 0.1%

pctchg_curr_sa_bal_avg_sa_bal_6m
Real number (ℝ)

MISSING  SKEWED 

Distinct29653
Distinct (%)69.3%
Missing7201
Missing (%)14.4%
Infinite0
Infinite (%)0.0%
Mean85.75323995
Minimum-1
Maximum1072937.649
Zeros339
Zeros (%)0.7%
Negative23058
Negative (%)46.1%
Memory size390.8 KiB
2023-04-05T23:08:43.134381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-0.9401736246
Q1-0.523275142
median-0.065638085
Q30.502561828
95-th percentile5.404803802
Maximum1072937.649
Range1072938.649
Interquartile range (IQR)1.02583697

Descriptive statistics

Standard deviation7522.945017
Coefficient of variation (CV)87.72782254
Kurtosis19352.29487
Mean85.75323995
Median Absolute Deviation (MAD)0.490425777
Skewness136.5094811
Sum3670152.916
Variance56594701.72
MonotonicityNot monotonic
2023-04-05T23:08:43.208992image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 687
 
1.4%
0 339
 
0.7%
-0.977011494 101
 
0.2%
-0.982758621 38
 
0.1%
-0.757614051 34
 
0.1%
-0.925287356 30
 
0.1%
6.085143452 25
 
0.1%
-0.936781609 22
 
< 0.1%
0.075860695 20
 
< 0.1%
-0.931034483 20
 
< 0.1%
Other values (29643) 41483
83.0%
(Missing) 7201
 
14.4%
ValueCountFrequency (%)
-1 687
1.4%
-0.999999992 1
 
< 0.1%
-0.99999981 1
 
< 0.1%
-0.999999788 1
 
< 0.1%
-0.999999686 2
 
< 0.1%
ValueCountFrequency (%)
1072937.649 2
< 0.1%
223312.6437 1
< 0.1%
145207.28 1
< 0.1%
104665.5025 1
< 0.1%
92238.56979 1
< 0.1%

product
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size390.8 KiB
Affluent_Card
21223 
Youth_Card
12824 
Mass_Card
9604 
HNI_Card
6349 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAffluent_Card
2nd rowMass_Card
3rd rowMass_Card
4th rowMass_Card
5th rowMass_Card

Common Values

ValueCountFrequency (%)
Affluent_Card 21223
42.4%
Youth_Card 12824
25.6%
Mass_Card 9604
19.2%
HNI_Card 6349
 
12.7%

Common Values (Plot)

2023-04-05T23:08:43.286576image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/